<h1 id="isPasted">2023 Autonomous Vehicle Report</h1>In 2020, Wevolver launched its first <a href="https://www.wevolver.com/article/2020.autonomous.vehicle.technology.report" target="_blank" rel="noopener noreferrer">Autonomous Vehicle Report</a> that provided a comprehensive knowledge foundation about the technologies enabling autonomous cars. We are now pleased to launch a new report that surveys the advances in this arena over the last three years. Further, we provide a snapshot comparison of four leading AV companies, their tech stacks, and approaches to understand how these technologies are applied in actual use cases. The report is augmented with interviews with the report sponsors, who provide deeper insights into the current state of autonomous vehicles, highlighting their priorities, challenges, and leadership objectives.&nbsp;The report examines autonomy from the perspective of passenger vehicles, following the approach of the previous report. However, many of the technologies mentioned are also relevant for other autonomous vehicle types that are making a significant impact in industries and applications such as last-mile delivery, warehouse and logistics, agriculture, mining, search and rescue, and healthcare.&nbsp;To create this report, we interviewed dozens of industry experts and collaborated with technical researchers and writers from around the world. We have attempted to cover all relevant technologies; however, due to space constraints, we had to limit some areas.&nbsp;This report was made possible by the generous support of its sponsors, the tireless effort of the Wevolver team, the expertise and generosity of our consulting experts, and the attention to detail of our writers, researchers, and designers.We hope you find value in this report, and we look forward to continuing to make this critical knowledge available for all.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAwODIwOTIwMDE1LU1pdHN1YmlzaGkgQ2hlbWljYWwgR3JvdXAgIEdyb3d0aCBHYXJhZ2UgIE9wZW4gSW5ub3ZhdGlvbiBQcm9ncmFtICg2OTQgeCA0MzIgcHgpICg5MDEgeCA1NjEgcHgpLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib"><iframe width="540" height="450" src="https://c8056756.sibforms.com/serve/MUIFAMBWtqlAziu5EwFUIjLCWmRdzCiwOJRx3R3LyYkfG1dfYIvOKLn1dfBY8M58jYUZY8sQm7DnIOmrBjZ93ycsAv4ICzMbRD95I3S4FIWFM6EU4i3C7yzFNYn-Kfm0vJN96NgNO2_w4BQcrnOEwEVShkElbpBLjOT3ARKFBFADGHd-PDjMwJZI5avI3TUfr-xTC_fVunqO5MKo" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;&nbsp;&nbsp;</iframe><h2>Report Contributors</h2>Cassiano Ferro MoraesFlorianópolis, BrazilTechnical writer with an electrical engineering background and over five years of experience writing articles about electronics, renewable energy, and electric vehicles. Published multiple articles in IEEE explore, including publications in some of the most recognized conferences and journals of the power electronics industry. Vast experience writing articles in the field of electronics, renewable energy, power converters, hardware-in-the-loop, and electric vehicles at Write Choice.&nbsp;Dr. Miroslav MilovanovicNiš, SerbiaAssistant professor at the Faculty of Electronic Engineering, holding a PhD in Computer Science and Electrotechnics. Leader of the Laboratory for Intelligent Control within the Control Systems Department. Author of over 45 scientific publications, centered on Data Science and Deep Learning applications.Gustavo BruismaPato Branco, BrazilElectrical Engineer graduated at the Federal Technological University of Paraná (UTFPR) with MSc. degree in the same field with a deep focus on control systems for electric vehicles. Vast experience writing articles in the field of electronics, renewable energy, power converters, hardware-in-the-loop, and electric vehicles at Write Choice.&nbsp;Ana Carla SorgatoFlorianópolis, BrazilEnvironmental and Sanitary Engineer graduated at the Federal University of Santa Maria (UFSM) with a MSc. in Environmental Engineering from UFSC. Currently pursuing a Ph.D. in Environmental Engineering at the Federal University of Santa Catarina (UFSC) and writing articles about renewable energy, electric vehicles, and engineering at Write Choice.Ian DicksonLondon, United KingdomFreelance automotive journalist and editor with more than two decades’ experience in consumer media and branded content. Cutting his teeth as a road tester on What Car? – where he learnt the art of turning the complex into the simple – he quickly moved through the ranks and ended up editor of MSN Cars, at the time the UK’s largest motoring website. For the past 10 years, he’s been creating and developing content and strategies for brands like Porsche, Ferrari, Volvo Cars and HERE Technologies.Samir JaberLeipzig, GermanyContent Specialist with a background in engineering, nanotechnology, and scientific research. Samir has comprehensive experience working with major engineering and technology companies as a writer, editor, and digital marketing consultant. Featured author in 30+ industrial magazines with a focus on IoT, nanotechnology, materials science, engineering, and sustainability. Samir is also an award-winning engineering researcher in the fields of nanofabrication and microfluidics. Editor-in-Chief of the Wevovler 2023 Edge AI Report.Danny ShapiroRedwood City, United StatesDanny Shapiro is NVIDIA’s Vice President of Automotive, focusing on solutions that enable faster and better design of automobiles, as well as in-vehicle solutions for infotainment, navigation and driver assistance. He's a 25-year veteran of the computer graphics and semiconductor industries, and has been with NVIDIA since 2009. Prior to NVIDIA, Danny served in marketing, business development and engineering roles at ATI, 3Dlabs, Silicon Graphics and Digital Equipment. He holds a BSE in electrical engineering and computer science from Princeton University and an MBA from the Hass School of Business at UC Berkeley. He lives in Northern California, where his home solar panel system charges his electric car.Alexander WischnewskiMunich, GermanyManaging Director and Co-Founder of, driveblocks, a modular, scalable, robust and safe platform for autonomous driving with a focus on commercial vehicle applications. Former PhD lead for the TUM Autonomous Motorsport team.&nbsp;Matteo BaraleMilan, ItalyCo-CEO of autonomous mobility startup, PIX MOVING. Design strategy expert with experience in robotics, industrial design, transportation, architecture, titled Technology Pioneer by World Economic Forum.&nbsp;David WebbLondon, United KingdomHead of Innovation at Centre for Connected and Autonomous Vehicles. David Webb is Head of Innovation for the UK Government’s Centre for Connected &amp; Autonomous Vehicles. CCAV works across government to support the UK’s developing connected and automated vehicle market. CCAV believes that CAVS could change the way we travel, making road transport safer, smoother and more accessible to all. David has a Masters in Aerospace Engineering from Queen Mary, University of London and has spent the last 10 years working for the Ministry of Defence in a variety of technical, analytical and engagement roles.&nbsp;John SoldatosAthens, GreeceHonorary Research Fellow at the University of GlasgowJohn Soldatos holds a Ph.D. in Electrical &amp; Computer Engineering from the National Technical University of Athens (2000) and is currently an Honorary Research Fellow at the University of Glasgow, UK (2014-present). He was Associate Professor and Head of the Internet of Things (IoT) Group at the Athens Information Technology (AIT), Greece (2006–2019), and Adjunct Professor at the Carnegie Mellon University, Pittsburgh, PA (2007–2010).&nbsp;He has significant experience working closely with large multi-national industries (e.g., IBM, INTRACOM, INTRASOFT International) as an R&amp;D consultant and delivery specialist while being a scientific advisor to various high-tech startup enterprises. Dr. Soldatos is an expert in Internet-of-Things (IoT) and Artificial Intelligence (AI) technologies and applications, including IoT/AI applications in smart cities, finance (Finance 4.0), and industry (Industry 4.0).&nbsp;Jess MileyBerlin, Germany&nbsp;Content Director at WevolverContent specialist with a background in architecture and design. Jess has experience working with neuro-tech startups, animated video studios, and news sites as a writer, editor, and business innovation consultant.&nbsp;The text was further contributed to by our report sponsors and partner.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAxMTE4ODczNjgzLXNwb25zb3JzIGxvZ29zLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib"><h3 dir="ltr" id="isPasted">Click through to read each of the report's chapters.</h3>2023 Autonomous Vehicle ReportAutonomous Vehicle Introduction<a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-sensing-technologies/draft" target="_blank">Chapter 1: Sensing Technologies</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-thinking-and-learning/draft" target="_blank">Chapter 2: Thinking and Learning</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-edge-computing-and-real-time-operating-systems-for-autonomous-vehicles/draft" target="_blank" rel="noopener noreferrer">Chapter 3: Edge Computing and Real-time Operating Systems for Autonomous Vehicles</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-communication-and-connectivity/draft" target="_blank" rel="noopener noreferrer">Chapter 4: Communication and Connectivity</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-security/draft" target="_blank" rel="noopener noreferrer">Chapter 5: Security</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-tech-stack-review/draft" target="_blank" rel="noopener noreferrer">Chapter 6: Autonomous Vehicle Tech Stack Review</a>Leadership Interviews<a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-accelerating-av-development-through-customer-collaboration/draft" target="_blank">Interview with Mouser&nbsp;</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-building-trust-in-autonomous-driving-navigating-future-reliability-and-milestone-achievements/draft" target="_blank">Interview with Murata&nbsp;</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-the-role-of-pcb-in-shaping-autonomous-vehicle-development/draft" target="_blank">Interview with MacroFab</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-exploring-the-future-of-high-performance-computing-in-autonomous-vehicles/draft" target="_blank">Interview with Nexperia</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-driving-global-standards/draft" target="_blank">Interview with SAE International</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-advancing-open-source-development-in-the-automotive-industry/draft" target="_blank">Interview with Autoware Foundation</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-insights-from-nvidia-about-artifical-intelligence-in-avs/draft" target="_blank">Interview with NVIDIA</a>

<h1 id="isPasted">Autonomous Vehicle Report</h1>In 2020, Wevolver launched its first <a href="https://www.wevolver.com/article/2020.autonomous.vehicle.technology.report" target="_blank" rel="noopener noreferrer">Autonomous Vehicle Report</a> that provided a comprehensive knowledge foundation about the technologies enabling autonomous cars. We are now pleased to launch a new report that surveys the advances in this arena over the last three years. Further, we provide a snapshot comparison of four leading AV companies, their tech stacks, and approaches to understand how these technologies are applied in actual use cases. The report is augmented with interviews with the report sponsors, who provide deeper insights into the current state of autonomous vehicles, highlighting their priorities, challenges, and leadership objectives.&nbsp;The report examines autonomy from the perspective of passenger vehicles, following the approach of the previous report. However, many of the technologies mentioned are also relevant for other autonomous vehicle types that are making a significant impact in industries and applications such as last-mile delivery, warehouse and logistics, agriculture, mining, search and rescue, and healthcare.&nbsp;To create this report, we interviewed dozens of industry experts and collaborated with technical researchers and writers from around the world. We have attempted to cover all relevant technologies; however, due to space constraints, we had to limit some areas.&nbsp;This report was made possible by the generous support of its sponsors, the tireless effort of the Wevolver team, the expertise and generosity of our consulting experts, and the attention to detail of our writers, researchers, and designers.We hope you find value in this report, and we look forward to continuing to make this critical knowledge available for all.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzAwODIwOTIwMDE1LU1pdHN1YmlzaGkgQ2hlbWljYWwgR3JvdXAgIEdyb3d0aCBHYXJhZ2UgIE9wZW4gSW5ub3ZhdGlvbiBQcm9ncmFtICg2OTQgeCA0MzIgcHgpICg5MDEgeCA1NjEgcHgpLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib"><iframe width="540" height="450" src="https://c8056756.sibforms.com/serve/MUIFAMBWtqlAziu5EwFUIjLCWmRdzCiwOJRx3R3LyYkfG1dfYIvOKLn1dfBY8M58jYUZY8sQm7DnIOmrBjZ93ycsAv4ICzMbRD95I3S4FIWFM6EU4i3C7yzFNYn-Kfm0vJN96NgNO2_w4BQcrnOEwEVShkElbpBLjOT3ARKFBFADGHd-PDjMwJZI5avI3TUfr-xTC_fVunqO5MKo" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</iframe><h2>Report Contributors</h2>Cassiano Ferro MoraesFlorianópolis, BrazilTechnical writer with an electrical engineering background and over five years of experience writing articles about electronics, renewable energy, and electric vehicles. Published multiple articles in IEEE explore, including publications in some of the most recognized conferences and journals of the power electronics industry. Vast experience writing articles in the field of electronics, renewable energy, power converters, hardware-in-the-loop, and electric vehicles at Write Choice.&nbsp;Dr. Miroslav MilovanovicNiš, SerbiaAssistant professor at the Faculty of Electronic Engineering, holding a PhD in Computer Science and Electrotechnics. Leader of the Laboratory for Intelligent Control within the Control Systems Department. Author of over 45 scientific publications, centered on Data Science and Deep Learning applications.Gustavo BruismaPato Branco, BrazilElectrical Engineer graduated at the Federal Technological University of Paraná (UTFPR) with MSc. degree in the same field with a deep focus on control systems for electric vehicles. Vast experience writing articles in the field of electronics, renewable energy, power converters, hardware-in-the-loop, and electric vehicles at Write Choice.&nbsp;Ana Carla SorgatoFlorianópolis, BrazilEnvironmental and Sanitary Engineer graduated at the Federal University of Santa Maria (UFSM) with a MSc. in Environmental Engineering from UFSC. Currently pursuing a Ph.D. in Environmental Engineering at the Federal University of Santa Catarina (UFSC) and writing articles about renewable energy, electric vehicles, and engineering at Write Choice.Ian DicksonLondon, United KingdomFreelance automotive journalist and editor with more than two decades’ experience in consumer media and branded content. Cutting his teeth as a road tester on What Car? – where he learnt the art of turning the complex into the simple – he quickly moved through the ranks and ended up editor of MSN Cars, at the time the UK’s largest motoring website. For the past 10 years, he’s been creating and developing content and strategies for brands like Porsche, Ferrari, Volvo Cars and HERE Technologies.Samir JaberLeipzig, GermanyContent Specialist with a background in engineering, nanotechnology, and scientific research. Samir has comprehensive experience working with major engineering and technology companies as a writer, editor, and digital marketing consultant. Featured author in 30+ industrial magazines with a focus on IoT, nanotechnology, materials science, engineering, and sustainability. Samir is also an award-winning engineering researcher in the fields of nanofabrication and microfluidics. Editor-in-Chief of the Wevovler 2023 Edge AI Report.Danny ShapiroRedwood City, United StatesDanny Shapiro is NVIDIA’s Vice President of Automotive, focusing on solutions that enable faster and better design of automobiles, as well as in-vehicle solutions for infotainment, navigation and driver assistance. He's a 25-year veteran of the computer graphics and semiconductor industries, and has been with NVIDIA since 2009. Prior to NVIDIA, Danny served in marketing, business development and engineering roles at ATI, 3Dlabs, Silicon Graphics and Digital Equipment. He holds a BSE in electrical engineering and computer science from Princeton University and an MBA from the Hass School of Business at UC Berkeley. He lives in Northern California, where his home solar panel system charges his electric car.Alexander WischnewskiMunich, GermanyManaging Director and Co-Founder of, driveblocks, a modular, scalable, robust and safe platform for autonomous driving with a focus on commercial vehicle applications. Former PhD lead for the TUM Autonomous Motorsport team.&nbsp;Matteo BaraleMilan, ItalyCo-CEO of autonomous mobility startup, PIX MOVING. Design strategy expert with experience in robotics, industrial design, transportation, architecture, titled Technology Pioneer by World Economic Forum.&nbsp;David WebbLondon, United KingdomHead of Innovation at Centre for Connected and Autonomous Vehicles. David Webb is Head of Innovation for the UK Government’s Centre for Connected &amp; Autonomous Vehicles. CCAV works across government to support the UK’s developing connected and automated vehicle market. CCAV believes that CAVS could change the way we travel, making road transport safer, smoother and more accessible to all. David has a Masters in Aerospace Engineering from Queen Mary, University of London and has spent the last 10 years working for the Ministry of Defence in a variety of technical, analytical and engagement roles.&nbsp;John SoldatosAthens, GreeceHonorary Research Fellow at the University of GlasgowJohn Soldatos holds a Ph.D. in Electrical &amp; Computer Engineering from the National Technical University of Athens (2000) and is currently an Honorary Research Fellow at the University of Glasgow, UK (2014-present). He was Associate Professor and Head of the Internet of Things (IoT) Group at the Athens Information Technology (AIT), Greece (2006–2019), and Adjunct Professor at the Carnegie Mellon University, Pittsburgh, PA (2007–2010).&nbsp;He has significant experience working closely with large multi-national industries (e.g., IBM, INTRACOM, INTRASOFT International) as an R&amp;D consultant and delivery specialist while being a scientific advisor to various high-tech startup enterprises. Dr. Soldatos is an expert in Internet-of-Things (IoT) and Artificial Intelligence (AI) technologies and applications, including IoT/AI applications in smart cities, finance (Finance 4.0), and industry (Industry 4.0).&nbsp;Jess MileyBerlin, Germany&nbsp;Content Director at WevolverContent specialist with a background in architecture and design. Jess has experience working with neuro-tech startups, animated video studios, and news sites as a writer, editor, and business innovation consultant.&nbsp;The text was further contributed to by our report sponsors and partner.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1701276054993-Untitled+%28600+x+200+px%29+%281%29.png" style="width: 300px;" class="fr-fic fr-dib"><h2 id="isPasted">Leadership Interviews</h2><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-accelerating-av-development-through-customer-collaboration" target="_blank" rel="noopener noreferrer">Interview with Mouser</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-building-trust-in-autonomous-driving-navigating-future-reliability-and-milestone-achievements" target="_blank" rel="noopener noreferrer">Interview with Murata</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-the-role-of-pcb-in-shaping-autonomous-vehicle-development" target="_blank" rel="noopener noreferrer">Interview with MacroFab</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-exploring-the-future-of-high-performance-computing-in-autonomous-vehicles" target="_blank" rel="noopener noreferrer">Interview with Nexperia</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-driving-global-standards" target="_blank" rel="noopener noreferrer">Interview with SAE International</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-advancing-open-source-development-in-the-automotive-industry" target="_blank" rel="noopener noreferrer">Interview with Autoware Foundation</a><a href="https://www.wevolver.com/article/2023-autonomous-vehicle-report-interview-insights-from-nvidia-about-artifical-intelligence-in-avs" target="_blank" rel="noopener noreferrer">Interview with NVIDIA</a>

Introduction

Sensing Technologies

Thinking and Learning

EDGE and RTOS

Communication and Connectivity

Security

Tech Stack

Examining the latest developments in self-driving vehicles.

Autonomous Vehicle Technology Report

This article was first published on <a href="https://news.mit.edu/2022/battery-free-wireless-underwater-camera-0926" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>. &nbsp;<hr>Scientists estimate that more than 95 percent of Earth&rsquo;s oceans have never been observed, which means we have seen less of our planet&rsquo;s ocean than we have the far side of the moon or the surface of Mars.The high cost of powering an underwater camera for a long time, by tethering it to a research vessel or sending a ship to recharge its batteries, is a steep challenge preventing widespread undersea exploration.MIT researchers have taken a major step to overcome this problem by developing a battery-free, wireless underwater camera that is about 100,000 times more energy-efficient than other undersea cameras. The device takes color photos, even in dark underwater environments, and transmits image data wirelessly through the water.The autonomous camera is powered by sound. It converts mechanical energy from sound waves traveling through water into electrical energy that powers its imaging and communications equipment. After capturing and encoding image data, the camera also uses sound waves to transmit data to a receiver that reconstructs the image.&nbsp;Because it doesn&rsquo;t need a power source, the camera could run for weeks on end before retrieval, enabling scientists to search remote parts of the ocean for new species. It could also be used to capture images of ocean pollution or monitor the health and growth of fish raised in aquaculture farms.&ldquo;One of the most exciting applications of this camera for me personally is in the context of climate monitoring. We are building climate models, but we are missing data from over 95 percent of the ocean. This technology could help us build more accurate climate models and better understand how climate change impacts the underwater world,&rdquo; says Fadel Adib, associate professor in the Department of Electrical Engineering and Computer Science and director of the Signal Kinetics group in the MIT Media Lab, and senior author of a new paper on the system.Joining Adib on the paper are co-lead authors and Signal Kinetics group research assistants Sayed Saad Afzal, Waleed Akbar, and Osvy Rodriguez, as well as research scientist Unsoo Ha, and former group researchers Mario Doumet and Reza Ghaffarivardavagh. The paper is <a href="https://www.nature.com/articles/s41467-022-33223-x" target="_blank">published today in Nature Communications</a>.<iframe src="https://www.youtube.com/embed/kyVZ1ll6_qY?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-gtm-yt-inspected-7="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" style="width: 768px; height: 433px;"></iframe><h2 id="isPasted">Going battery-free</h2>To build a camera that could operate autonomously for long periods, the researchers needed a device that could harvest energy underwater on its own while consuming very little power.The camera acquires energy using transducers made from piezoelectric materials that are placed around its exterior. Piezoelectric materials produce an electric signal when a mechanical force is applied to them. When a sound wave traveling through the water hits the transducers, they vibrate and convert that mechanical energy into electrical energy.Those sound waves could come from any source, like a passing ship or marine life. The camera stores harvested energy until it has built up enough to power the electronics that take photos and communicate data.To keep power consumption as a low as possible, the researchers used off-the-shelf, ultra-low-power imaging sensors. But these sensors only capture grayscale images. And since most underwater environments lack a light source, they needed to develop a low-power flash, too.&ldquo;We were trying to minimize the hardware as much as possible, and that creates new constraints on how to build the system, send information, and perform image reconstruction. It took a fair amount of creativity to figure out how to do this,&rdquo; Adib says.They solved both problems simultaneously using red, green, and blue LEDs. When the camera captures an image, it shines a red LED and then uses image sensors to take the photo. It repeats the same process with green and blue LEDs.Even though the image looks black and white, the red, green, and blue colored light is reflected in the white part of each photo, Akbar explains. When the image data are combined in post-processing, the color image can be reconstructed.&ldquo;When we were kids in art class, we were taught that we could make all colors using three basic colors. The same rules follow for color images we see on our computers. We just need red, green, and blue &mdash; these three channels &mdash; to construct color images,&rdquo; he says.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1664333175160-MIT-Underwater-Camera-02.jpg" style="width: 766px;" class="fr-fic fr-dib">Fadel Adib (left) associate professor in the Department of Electrical Engineering and Computer Science and director of the Signal Kinetics group in the MIT Media Lab, and Research Assistant Waleed Akbar display the battery-free wireless underwater camera that their group developed. Image: Adam Glanzman<h2>Sending data with sound</h2>Once image data are captured, they are encoded as bits (1s and 0s) and sent to a receiver one bit at a time using a process called underwater backscatter. The receiver transmits sound waves through the water to the camera, which acts as a mirror to reflect those waves. The camera either reflects a wave back to the receiver or changes its mirror to an absorber so that it does not reflect back.A hydrophone next to the transmitter senses if a signal is reflected back from the camera. If it receives a signal, that is a bit-1, and if there is no signal, that is a bit-0. The system uses this binary information to reconstruct and post-process the image.&ldquo;This whole process, since it just requires a single switch to convert the device from a nonreflective state to a reflective state, consumes five orders of magnitude less power than typical underwater communications systems,&rdquo; Afzal says.The researchers tested the camera in several underwater environments. In one, they captured color images of plastic bottles floating in a New Hampshire pond. They were also able to take such high-quality photos of an African starfish that tiny tubercles along its arms were clearly visible. The device was also effective at repeatedly imaging the underwater plant&nbsp;Aponogeton ulvaceus in a dark environment over the course of a week to monitor its growth.Now that they have demonstrated a working prototype, the researchers plan to enhance the device so it is practical for deployment in real-world settings. They want to increase the camera&rsquo;s memory so it could capture photos in real-time, stream images, or even shoot underwater video.They also want to extend the camera&rsquo;s range. They successfully transmitted data 40 meters from the receiver, but pushing that range wider would enable the camera to be used in more underwater settings.&ldquo;This will open up great opportunities for research both in low-power IoT devices as well as underwater monitoring and research,&rdquo; says Haitham Al-Hassanieh, an assistant professor of electrical and computer engineering at the University of Illinois Urbana-Champaign, who was not involved with this research.<hr>&quot;Reprinted with permission of&nbsp;<a href="https://news.mit.edu/2022/battery-free-wireless-underwater-camera-0926" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>&quot;&nbsp;

A battery-free, wireless underwater camera developed at MIT could have many uses, including climate modeling. “We are missing data from over 95 percent of the ocean. This technology could help us build more accurate climate models and better understand how climate change impacts the underwater world,” says Associate Professor Fadel Adib. Image: Adam Glanzman

The device could help scientists explore unknown regions of the ocean, track pollution, or monitor the effects of climate change.

Engineers build a battery-free, wireless underwater camera

<h3>Navigation without GPS: how Carnegie Mellon University's autonomous submarine tracks velocity, attitude and heading underwater</h3>For engineering and computer science students at Carnegie Mellon University (CMU) in Pittsburgh, Pennsylvania, the learning experience extends beyond the usual program of lectures, seminars, and written assignments. At CMU, students have the chance to apply their newly acquired knowledge in real-world product development that uses an array of cutting-edge technologies.That's because CMU hosts a successful robotics project in which a team of students develops a marine robot to compete in the prestigious RoboSub competition organized by the RoboNation educational non-profit. The CMU team's <a href="https://tartanauv.com/" rel="noopener noreferrer" target="_blank">TartanAUV</a> fully autonomous submarine is now in its second generation: the new vehicle is a substantial technical upgrade on the first, which marked CMU’s first entry in the RoboSub competition.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjU1Mjc0Mzk2NjU1LXRhdXYtMTAyNHg3NjguanBlZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 300px;" class="fr-fic fr-dib">As the students explain below, the competition demands extremely precise, real-time location and orientation information underwater, in 3D. And a crucial element of the upgrade has been the integration of an Xsens <a href="https://www.xsens.com/mti-200" rel="noopener noreferrer" target="_blank">MTi-200</a> Vertical Reference Unit (VRU), which provides accurate, synchronized orientation and heading outputs even in the presence of strong magnetic interference.<h3>3D navigation: a challenging underwater task</h3>The annual RoboSub competition requires student teams to develop an autonomous underwater vehicle (AUV) and then test it on various tasks, which mimic the behaviors required of an AUV operating in the real world. These behaviors have visual, mechanical and logical dimensions. The sub is required to navigate underwater in a large pool of clear water, to identify objects such as gates, to calculate a pathway within and between tasks, and to perform specified maneuvers such as barrel rolls – all within a time limit of 15 minutes. Competition entrants are judged on their sub's success in completing tasks, and on the style with which it performs them.Since the sub navigates underwater, it cannot use satellite navigation (GPS) signals to track its location. This means that it must perform dead reckoning, calculating its position in 3D from a known starting point by continuously measuring its velocity, attitude, and heading.Theodore Chemel, the Engineering Lead of the CMU team, says that analysis of the performance of the first iteration of the TartanAUV sub, named Albatross, identified a substantial opportunity for improvement. 'Albatross dropped points because of the amount of drift in the dead reckoning calculations, causing the sub to deviate from the ideal pathway and slowing the completion of tasks. So a top priority for the new Kingfisher version of TartanAUV was to improve the guidance, navigation and control (GNC) system,' he says.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjU1Mjc0NDE4MjQ1LWtpbmdzZmlzaGVyIHJlc2l6ZWQucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib">KINGFISHER (2020)Computing capacity imposed no limitation on the sub’s performance: the upgraded Kingfisher sub includes a powerful new Nvidia Jetson AGX Xavier single-board computer. This gives enough computing bandwidth to perform highly complex synchronization and fusion of multiple navigation sensor inputs. This gave the CMU student engineers the opportunity to adopt two new hardware components which, in combination, have produced a huge improvement in navigation performance.One is the Xsens MTi-200 VRU. Theodore Chemel says that the high level of integration inside the MTi unit was a big attraction for the TartanAUV team. 'The software inside the MTi-200 does an outstanding job of error correction and synchronization of the 3D measurements produced by the unit’s accelerometers, gyroscopes, and magnetometer, so the orientation data output that it produces is extremely accurate. At a maximum 400Hz output data rate, it provides more than enough precision for our needs.'The other big advantage of the MTi-200 is its high immunity to magnetic interference. RoboSub competitions are normally held in large indoor pools: the Albatross sub competed in a US Navy test tank in a hangar with vast metal gantries overhead. Interference from the mass of steel badly affected the heading measurements provided by the previous position sensor.There are no such problems with the MTi-200. Theodore Chemel says that, before selecting the MTi-200, the CMU team tested its performance by operating it close to a very large magnet. He says the VRU's performance was 'rock solid. The Xsens Active Heading Stabilization (AHS) feature works really well to filter out interference and give an accurate heading measurement in all environments.’The second innovation in navigation hardware was to add a Teledyne Pathfinder Doppler Velocity Log (DVL), a type of acoustic sensor which provides extremely accurate measurements of linear velocity. But while this device is accurate, it offers very low resolution: its update rate is only 10Hz. So the CMU team uses the power of the Jetson computer to fuse and synchronize the IMU and DVL outputs: the IMU measurements fill in the gaps between the low-frequency DVL measurements. The MTi-200's highly accurate clock provides the master timing signal, triggering the DVL to perform time-stamped velocity measurements.<iframe width="640" height="360" src="https://www.youtube.com/embed/mG4iif9GNVw?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</iframe><h3>Upgraded sub offers promising performance improvements</h3>The results of the substantial hardware upgrade in the Kingfisher variant of the TartanAUV are looking promising as the CMU team prepares to compete in the 2022 RoboSub competition (25-31 July, Washington DC). Theodore Chemel says, 'The real test of the sub's performance is when it is in competition and performing the specified tasks, but our testing shows that the GNC system is now performing exactly the way we want it to. Over an 8-minute test run, deviation from the plotted path can hardly be seen by the eye. Thanks to the MTi-200 and the DVL, we are very happy with the way the new TartanAUV performs dead reckoning in 3D.'It's not only the navigation system in the TartanAUV which is impressive – the sub draws on the talents of a broad team of mechanical and electrical engineering and computer science students. As they prepare to launch into competition in California, they can already feel proud of the outstanding use to which they have put the MTi-200 VRU.For information about RoboNation's RoboSub program,&nbsp;<a href="https://robonation.org/programs/robosub" rel="noopener noreferrer" target="_blank">click here</a>.The Tartan AUV project is an initiative of Carnegie Mellon University -More information about the Tartan AUV may be found&nbsp;<a href="https://tartanauv.com/" rel="noopener noreferrer" target="_blank">here</a>.

with Xsens MTi-200

Navigation without GPS: Carnegie Mellon University's autonomous submarine

Tests conducted by Cornell and the U.S. Navy used new algorithms to outperform state-of-the-art programming for autonomous underwater sonar imaging, significantly improving the speed and accuracy for identifying objects such as explosive mines, sunken ships, airplane black boxes, pipelines and corrosion on ship hulls.Sea reconnaissance is filled with challenges that include murky waters, unpredictable conditions and vast areas of subaquatic terrain. Sonar is the preferred imaging method in most cases, but acoustic waves can be difficult to decipher, often requiring different angles and views of an object before it can be identified.&ldquo;If you have a lot of targets and they&rsquo;re distributed over a large region, it takes a long time to classify them all,&rdquo; said Silvia Ferrari, the John Brancaccio Professor of Mechanical and Aerospace Engineering, who led the research published May 24 in the journal&nbsp;<a href="https://ieeexplore.ieee.org/document/9780576" target="_blank">IEEE Journal of Oceanic Engineering</a>. &ldquo;Sometimes an autonomous underwater vehicle won&#39;t be able to finish the mission because it has limited battery life.&rdquo;To improve the capability of these vehicles, Ferrari&rsquo;s research group teamed up with the Naval Surface Warfare Center, Panama City, and the Naval Undersea Warfare Center, Newport, Virginia. The team created and tested a new imaging approach called informative multi-view planning, which integrates information about where objects might be located with sonar processing algorithms that decide the optimal views, and the most efficient path to obtain those views. The planning algorithms take into account the sonar sensor&rsquo;s field-of-view geometry along with each target&rsquo;s position and orientation, and can make on-the-fly adjustments based on current sea conditions.In computer simulated tests, the research team&rsquo;s algorithms competed against state-of-the-art imaging methods to complete multi-target classification tasks. The new algorithms were able to complete the tasks in just half the time, and with a 93% improvement in accuracy of identifying targets. In a second test in which the targets were more randomly scattered, the new algorithms performed the imaging task more than 11% faster, and with 33% more accuracy.&ldquo;Until these algorithms, we were never able to account for the orientation and some of the more complicated automatic target variables that influence the quality of the images,&rdquo; Ferrari said. &ldquo;Now we can accomplish the same imaging tasks with higher accuracy and in less time.&rdquo;As a final test, the algorithms were programmed into a REMUS-100 autonomous underwater vehicle tasked with identifying 40 targets scattered within an area of St. Andrew Bay off the coast of Florida. Performing in its first undersea trial, the new algorithms achieved the same speed as the state-of-the-art algorithms, and with equal or superior classification performance.&ldquo;Demonstrating the developed algorithms using an actual vehicle in sea trials is a very exciting achievement,&rdquo; said Jane Jaejeong Shin, Ph.D. &rsquo;21, who is now an assistant professor of mechanical and aerospace engineering at the University of Florida. &ldquo;This result shows the potential of these algorithms to be extended and applied more generally in similar underwater survey missions.&rdquo;

Tests conducted by Cornell and the U.S. Navy used new algorithms to outperform state-of-the-art programming for autonomous underwater sonar imaging, significantly improving the speed and accuracy for identifying objects such as explosive mines, sunken ships, airplane black boxes, pipelines, etc.

Cornell, US Navy raise bar for autonomous underwater imaging

Wireless energy transmission, the dream of visionaries including Nikola Tesla with his Wardenclyffe Tower experiments, is today a reality. From completely-sealed electric toothbrushes to smartphones capable of charging when just thrown down onto a mat at the end of the day, there are plenty of examples of commercially-viable wireless power systems in everyday life &mdash; and still more on the horizon, including proposals for energising electric vehicles while they travel or robots as they roam.The majority of these, however, rely on electromagnetic transmission &mdash; an approach which works perfectly well over the air, but begins to encounter difficulties when faced with transmission through other media such as living tissue or water. What could be an ideal way to charge implanted electronics or undersea sensor networks becomes significantly more challenging &mdash; which is why a team of researchers from a number of Korean institutions have turned to acoustic energy transfer instead, switching from electromagnetic radiation to ultrasound as the energy source.<h1>The sound of power</h1>The team, led by the Korea Institute of Science and Technology (KIST), isn&rsquo;t the first to look at &mdash; or even succeed at &mdash; wireless energy transmission via ultrasound. Previous approaches, however, have been extremely limited in either the distance over which the energy can be transmitted or the amount of energy usable at the receiver &mdash; or, typically, both.The prototype developed by the researchers, by contrast, offers a considerable improvement over the state-of-the-art in both respects. Built using a five-layer design &mdash; a flexible electrode upper, a fixed area, a triboelectric layer, a novel ferroelectric layer, and a bottom electrode &mdash; the receiver sheets generate energy through movement induced by a 40kHz ultrasound signal, but represent only part of the gain in performance reported in the work.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjUyODEzNjUzNzY0LWVzczQuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib" alt="A diagram of a prototype Acoustic Energy Transmission (AET) receiver, showing the five layers: Flexible electronics, fixed part, triboelectric layer, ferroelectric layer, and bottom electrode. A photograph of actual prototypes are seen to the right, marked with an outer fixed area frame and an inner active area.">The prototype AETs developed by the KIST-led team are made up of five layers, and produce energy from movement as triboelectric generators. The remainder, the team explains, comes from a switch from a sinusoidal acoustic wave to a square wave &mdash; an approach which, combined with the addition of piezoelectric PNM-PT crystals to the receiver as the ferroelectric layer, considerably boosts the output voltage available to connected electronics. Interestingly, the researchers conclude that the boosted voltage comes not from the piezoelectric effect directly but from a boost to the triboelectric effect.&ldquo;It can be seen that our device is mode-free,&rdquo; the team explains, &ldquo;and frequency independent. This is vital for its practical use, because unlike piezoelectric type receivers, our device does not necessitate a precisely matched ultrasound transducer.&rdquo;<h1>Switched on by sound</h1>To prove not only the core concept but also its applicability in simulations of various real-world use cases, the team built receiver prototypes and placed them in a range of materials: A lump of pork, used as a stand-in for human tissue in the case of recharging or directly powering implanted electronic devices; metal, acrylic, medium-density fiberboard (MDF), and plywood, to show its ability to transmit energy through a range of housing materials including those which would block electromagnetic radiation; and a tank of water, to showcase the system&rsquo;s potential for powering sub-aquatic drones or sensor networks ill-suited to other wireless energy transfer approaches.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjUyODEzNjY3MDY4LWVzczIuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib" alt="Photographs of three prototypes: A trapezoidal 3D-printed prototype with five receiver faces connected to an electronic circuit and a CC2650 development board; the same receiver connected to two 200-LED matrices, with an ultrasonic transducer postioned 6cm away above a water tank; and the same receiver with wireless sensors fitted transmitting to a tablet PC over Bluetooth with the transducer 6cm away above the same water tank.">The team built several prototypes to prove the device&#39;s capabilities for useful energy transfer, including Bluetooth-connected sensor networks located under 6cm of water.The results are undeniably impressive. The body-implanted version proved capable of delivering sufficient power to drive implantable electronic devices without damage to the surrounding tissue and with the ultrasound emissions kept well within FDA-approved limits for use on patients; the system successfully transmitted though all the housing materials, representing the bulk of materials used in commercial and industrial electronic systems; and energy transmission worked perfectly through water.The latter experiments are worth further analysis. The team created a 3D-printed trapezoidal structure with prototype energy receiving sheets making up five of its faces, then fitted a range of wireless sensors designed for water quality monitoring &mdash; measuring metrics including temperature, carbon dioxide levels, pressure, and humidity. These were then powered using a transmitter 6cm (around 2.4&quot;) away &mdash; &ldquo;an order longer,&rdquo; the team notes, &ldquo;than the previous report.&rdquo;In further testing the team directly drove two matrices of 200 LEDs each at a brightness high enough to be observed under laboratory lighting, before concluding with a &ldquo;conclusive demonstration&rdquo; as to the approach&#39;s suitability for practical use: The replacement of the battery in a commercial Texas Instruments CC2650 Bluetooth Sensor Tag with an acoustic energy receiver which was capable of triggering Bluetooth transmission of sensor readings to a nearby tablet computer within a second of the ultrasound transmitter being energized.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjUyODEzNjc2Mzc0LWVzczMuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib" alt="A line graph showing the voltage produced by the AET system with four design changes: Only PTFE and sinusoidal wave; PTFE, <111> PMN-PT (up) and sinusoidal wave; only PTFE and square wave; and PTFE, <111> PMN-PT (up) and square wave. With each change, the voltage can be seen increasing in turn.">The team&#39;s approach makes two key changes to the previous state-of-the-art, the use of square wave signals and the addition of a ferroelectric layer, with excellent results.&ldquo;This study demonstrated that electronic devices can be driven by wireless power charging via ultrasonic waves,&rdquo; says Hyun-Cheol Song, PhD, who led the project. &ldquo;If the stability and efficiency of the device are further improved in the future, this technology can be applied to supply power wirelessly to implantable sensors or deep-sea sensors, in which replacing batteries is cumbersome.&rdquo;The team&rsquo;s work has been published under closed-access terms in the journal <cite><a href="https://pubs.rsc.org/en/content/articlelanding/2022/EE/D1EE02623B" target="_blank">Energy &amp; Environmental Science</a></cite>.<h1>Reference</h1>Hyun Soo Kim, &nbsp;Sunghoon Hur, Dong-Gyu Lee, Joonchul Shin, Huimin Qiao, Seunguk Mun, Hoontaek Lee, Wonkyu Moon, Yunseok Kim, Jeong Min Baik, Chong-Yun Kang, Jong Hoon Jung, and Hyun-Cheol Song: <cite>Ferroelectrically augmented contact electrification enables efficient acoustic energy transfer through liquid and solid media, Energy &amp; Environmental Science, Iss. 3 2022</cite>. DOI <a href="https://doi.org/10.1039/D1EE02623B" target="_blank">10.1039/D1EE02623B</a>.

An artist's impression of the proposed AET system being used to drive both underwater sensor networks and autonomous underwater vehicles (AUVs), using nothing but ultrasound signals from a passing boat on the surface.

A team of researchers in Korea has been working on functional acoustic energy transmission (AET) systems, and their latest paper details a major breakthrough: Prototypes capable of powering LEDs, sensors, and Bluetooth transmitters at range and through materials include metal, tissue, and water.

A move to ultrasonic acoustics for wireless energy transmission could power implants, underwater sensors, and more

Microplastics are of growing concern, both for human health and the broader ecology. With millions of tonnes of plastic waste entering the marine ecosystem ever year, solutions are needed urgently &mdash; and while initiatives to prevent the waste from entering the ecosystem in the first place, by moving away from single-use plastics and implementing stronger recycling requirements, are a vital step, they do nothing for the waste already floating around our oceans.Autonomous underwater vehicles (AUVs), however, can help address the latter. Equipped with suitable grabbers, AUVs could roam the seas to locate plastic waste and remove it for recycling or more proper disposal &mdash; but only if they can recognize it. That&rsquo;s where a team of researchers, working with the United Kingdom&rsquo;s Natural Environment Research Council, aims to help: Improving computer vision systems to give AUVs better skills in recognizing plastic waste in underwater environments.<h1>Smarter vision</h1>The researchers envision the control system of a plastic-hunting AUV as three blocks: An image enhancement block, specifically designed for the murky low-light conditions found under the sea; a recognition block, capable of discerning plastic waste from other underwater objects and locating them accurately; and a guidance block, which navigates the vehicle to the waste and coordinates its collection.Seeing the potential for boosted performance, first author Federico Zocco and colleagues concentrated their efforts on the image enhancement and recognition blocks. The team started by applying a state-of-the-art object detector class, EfficientDets, to the task of recognizing plastic waste and differentiating it from other undersea objects like fish.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ5OTY2OTMxNDIxLWRlYnJpczMuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib" alt="A picture showing a feed from an underwater camera with visible waste plastic, passing into a box marked &quot;underwater image enhancement&quot; before the enhanced images are passed to a box marked &quot;recognition&quot; and then the recognition outputs passed to a box marked &quot;guidance, navigation and control systems of both vehicle and gripper.&quot; A further box below shows the difference between three recognition systems: a classifier, with a class output; a detector, with class and position outputs; and a segmenter, with class, position, and shape outputs. A 3D model of an autonomous underwater vehicle is seen to the bottom-right.">Automated cleanup of plastic ocean waste could receive a boost from a new, more accurate version of EfficientDets running on autonomous underwater vehicles (AUVs). Created by a team working at Google Research, EfficientDets are designed to offer accurate object detection at a low latency &mdash; offering anything up to a ninefold size reduction and a forty-twofold drop in computational requirements than previous approaches. Zocco and colleagues, however, believed it possible to improve upon this &mdash; particularly in terms of specializing EfficientDets for the task at hand.Initially, the team concentrated on architectural modifications: Changing the number of weighted bi-directional feature pyramid network (BiFPN) layers, the number of convolutional layers, and scaling up parent detectors in order to find the best balance between latency and accuracy. Then, the resulting improved EfficientDets were trained on the Trash-ICRA19 dataset with biological, plastic, and remote-operated vehicle classes &mdash; before being trained again on a custom dataset, In-Water Plastic Bags and Bottles (WPBB), with 900 fully-annotated images of the target items recorded in a testing pool by a Chasing Dory drone.<h1>Better vision</h1>In addition to improving the object detection block, the team also investigated how the images themselves can be improved &mdash; taking the low-light captures of a AUV&rsquo;s camera feed and making them better-suited to object detection and classification.The team took the L2UWE framework detailed by Tunai Porto Marques and Alexandra Branzan Albu in 2020, designed for efficient enhancement of low-light underwater imagery, and applied it to a subset Trash-ICRA19 images which had been modified for simulated low-light conditions. While an improvement in accuracy was noted, it came at a considerable cost: &ldquo;L2UWE is too computationally demanding for real-time applications,&rdquo; the team noted, with the inference time per image reaching over 11 seconds when the framework was applied as a pre-processing step.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ5OTY2OTQ3OTM5LWRlYnJpczEuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib" alt="A graph showing a comparison between standard and improved EfficientDets: The improved version can be seen outperforming the standard version at each measurement, without an increase in latency. Below the graph is an example of a dark input image being processed through low-light image enhancement then through the detector; the final image shows an eel labelled &quot;bio: 91%&quot; and some debris labelled &quot;plastic: 80%.&quot;">The team&#39;s approach boosted the accuracy of EfficientDets measurably, without an increase in latency. A simpler approach was then tried: Just boosting the brightness of the image on a per-pixel basis, with no thought to enhancement at all. Doing so showed a notable increase in accuracy, though without analyzing each image and determining the amount of brightening required it&rsquo;s a rough approach at best.&ldquo;A more efficient approach,&rdquo; the team notes, &ldquo;is to tune the value of c [the increase in brightness applied to images] offline using genetic algorithms or particle swarm optimization and subsequently use it for low-light real-time marine debris detection within an automation pipeline.&rdquo;The team&rsquo;s overall results show promise: With EfficientDets already being considered state-of-the-art, a reported 1.2-2.6 per cent increase in average precision for the task of plastic waste recognition underwater with no increase in latency is a notable achievement &mdash; and the team has made it possible for others to improve the approach still further by publishing both the WPBB dataset and the project&rsquo;s source code <a href="https://github.com/fedezocco/MoreEffEffDetsAndWPBB-TensorFlow" target="_blank">on GitHub</a> under the permissive MIT license.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ5OTY2OTU3NzYzLWRlYnJpczIuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 300px;" class="fr-fic fr-dib" alt="Images of plastic bottles and bags floating in an underwater tank, captured from an autonomous underwater vehicle. Each has been labelled &quot;plastic bottle&quot; or &quot;plastic bag&quot; by the improved EfficientDets with confidence ranging from 95 to 99 per cent, with one 43 per cent outlier.">The WPBB dataset, captured using a commercial AUV in a tank and with real examples of waste plastics, has been released under a permissive license along with full source code for the project.The team&rsquo;s next step: Implementing the proposed detection pipeline on a physical AUV, integrated with the navigation and gripper control system for automated waste collection.The paper detailing the team&rsquo;s work has been made available <a href="https://arxiv.org/abs/2203.07155" target="_blank">on Cornell&rsquo;s arXiv preprint server</a> under open-access terms.<h1>References</h1>Federico Zocco, Ching-I Huang, Hsueh-Cheng Wang, Mohammad Omar Khyam, and Mien Van: <cite>Towards More Efficient EfficientDets and Low-Light Real-Time Marine Debris Detection, to be submitted to IEEE Robotics and Automation Letters</cite>. Preprint DOI <a href="https://arxiv.org/abs/2203.07155" target="_blank">arXiv:2203.07155</a> [cs.CV].Mingxing Tan, Ruoming Pang, and Quoc V. Le: <cite>EfficientDet: Scalable and Efficient Object Detection, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020</cite>. DOI <a href="https://doi.org/10.1109/cvpr42600.2020.01079" target="_blank">10.1109/cvpr42600.2020.01079</a>.Tunai Porto Marques and Alexandra Branzan Albu: <cite>L2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020</cite>. DOI <a href="https://doi.org/10.1109/CVPRW50498.2020.00277" target="_blank">10.1109/CVPRW50498.2020.00277</a>.

Plastic waste running from rivers to the seas is a growing problem, which will take a major clean-up to solve. Enter the AUVs.

With growing concern over microplastics from ocean waste, autonomous underwater vehicles — AUVs — have been proposed as a tool for cleaning up our seas, but only if they can pick the plastics out from the fish: Enter these tweaked EfficientDets, boosting accuracy for the task.

Automated ocean waste retrival the target for new, specialized open-source EfficientDets

An ROV camera is any visual imaging system that can be used on <a href="https://blueprintlab.com/blog/what-is-an-underwater-rov/" target="_blank">underwater ROVs</a> to provide the operator with a perception of the operating environment. The depth rating for an <a href="https://blueprintlab.com/products/underwater-rov-camera/" target="_blank">ROV camera</a> usually starts at 300m.Most ROVs have a main forward-facing camera for control of the vehicle. Some ROVs will then have additional, auxiliary cameras to provide another point of view. These cameras are sometimes mounted on another point of the vehicle or extended out from the vehicle using a &lsquo;boom mount&rsquo; (e.g. a camera on a pole sticking out to the side). If an ROV manipulator is in use, this manipulator will sometimes have a camera at the end-effector providing yet another point of view of the workspace. One should remember that underwater vision systems are usually monocular and therefore do not provide distance information (try catching a ball with one eye closed); development in this area using stereo vision and other sensors is a hot topic in underwater robotics and is currently being pursued by Blueprint Lab to enable more advanced use of <a href="https://blueprintlab.com/products/manipulators/" target="_blank">manipulator arms</a> and <a href="https://blueprintlab.com/products/rov-grippers/" target="_blank">ROV grippers</a>.<h2><style type="text/css" id="isPasted"></style><style type="text/css"></style>What Are The Different Types Of ROV Camera?</h2>There are two main types of underwater or ROV camera:<h3>1. Main ROV Camera</h3>The main ROV camera is the primary means of providing visual information to the ROV operator. These cameras are generally selected to be High-Definition and to have exceptional performance in low-light conditions. They are the primary camera used to pilot the vehicle and are forward-facing. Depending on the size of the vehicle, this camera may also be used for looking at objects of interest or there may be an additional camera for that purpose to deconflict from piloting operations.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1649419090826-image.png" style="width: 766px;" class="fr-fic fr-dib">An image from the forward-looking camera on the ROV SuBastian of the Schmidt Ocean InstituteSometimes they are fixed&hellip;&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1649419133804-image-1.png" style="width: 766px;" class="fr-fic fr-dib">An HD camera by ROV Innovations suitable for forward-facing main ROV camera use&hellip;other times they are attached to mechanisms (<a href="https://blueprintlab.com/products/underwater-rotator/" target="_blank">rotators and pan/tilt units</a>) to enable them to move left/right and up/down, providing a greater field of view to the operator.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1649419168373-image-2.png" style="width: 766px;" class="fr-fic fr-dib">The main ROV camera with tilt-function &ndash; the DTR-100Z from Bowtech&nbsp;<h3 id="isPasted">2. Auxiliary ROV Camera</h3>Auxiliary cameras are used to provide additional perspectives to that provided by the main, front ROV camera. Examples of where these are used are:<ul><li>A camera facing rearward to check the ROV tether condition or ensure the tether is not tangled during a complex manoeuvre.</li><li>A camera mounted on a corner of the ROV, or out on a boom and looking in towards the front of the ROV to provide a sense of distance when flying the ROV or using an ROV gripper or ROV manipulator.</li><li>A camera mounted on a manipulator arm to enable close vision of what the manipulator is being used for such as in <a href="https://blueprintlab.com/blog/top-uses-for-underwater-manipulators/" target="_blank">close visual inspections or complex interventions</a>.</li><li>A camera mounted on the side of the ROV to enable inspection of a structure while flying alongside it.</li></ul><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1649419205930-image-3.png" style="width: 766px;" class="fr-fic fr-dib">One of the auxiliary cameras on the ROV SuBastian provides an additional perspective of the ROV workspace.&nbsp;Auxiliary cameras often do not need to meet the same specifications as the main ROV camera and may additionally be limited by size constraints. Hence, they are often selected to be <a href="https://blueprintlab.com/products/underwater-rov-camera/" id="isPasted" target="_blank">pencil-style subsea cameras</a>. These cameras have the advantage of lower cost and smaller size.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1649419238477-image-4.png" style="width: 766px;" class="fr-fic fr-dib">The Micro IP Camera from Blueprint Lab (Outer Diameter 2.4cm, length ~9cm)&nbsp;<h2 id="isPasted"><style type="text/css" id="isPasted"></style><style type="text/css"></style>Considerations In Selecting An ROV Camera </h2>If you are selecting a camera for your underwater ROV or ROV manipulator, you should consider the following:<ul><li>Quality</li><li>Size (check out our <a href="https://blueprintlab.com/products/underwater-rov-camera/" target="_blank">miniature subsea camera</a> if this is a factor in your design)</li><li>Water Weight</li><li>Connector</li><li>Protocol</li><li>Performance in Low Light (sometimes additional illumination should be considered by adding <a href="https://blueprintlab.com/products/subsea-light/" target="_blank">ROV lights</a>, or selecting a camera with integrated LEDs)</li><li>Viewing Angle</li><li>Whether actuation (pan, tilt, complex motion) is required (if so, take a look at Blueprint Lab&rsquo;s<a href="https://blueprintlab.com/products/underwater-rotator/" target="_blank">&nbsp;rotator</a> and <a href="https://blueprintlab.com/products/manipulators/" target="_blank">manipulator</a> solutions)</li></ul>

An ROV camera is any visual imaging system that can be used on underwater ROVs to provide the operator with a perception of the operating environment. The depth rating for an ROV camera usually starts at 300m.

What is an ROV camera?

Doing things underwater has always been challenging. Human divers brave the pressures of the deep subsea environment, dealing with low light, poor visibility, and little room for error. Since the 1970s, technology developments gave rise to ROVs with robotic arms (aka &lsquo;<a href="https://blueprintlab.com/products/manipulators/" target="_blank">underwater manipulator arms&rsquo;</a>) to start accomplishing tasks underwater.Industries that use ROV manipulators include offshore energy, military, search and rescue, and marine science.Whilst not as dexterous as humans, these ROV manipulator systems are stronger and can go deeper than humans can dive. This ushered in a new era for offshore oil companies who could now install and maintain deeper installations.Originally, ROV manipulators were large and hydraulically powered. Today, whilst large hydraulic manipulators are still the workhorse of the ROV industry, electric systems have started to be released to the market. In particular, smaller electric ROV manipulators that are still highly dexterous have opened up new possibilities for the ROV community.Here are the top 9 uses of underwater ROV manipulators based on working with our clients here at Blueprint Lab.<h2>1. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Non-Destructive Testing (NDT)</h2><a href="https://en.wikipedia.org/wiki/Nondestructive_testing" rel="noreferrer noopener nofollow" target="_blank">Non-Destructive Testing</a> (NDT), and sometimes called NDE or NDI for examination and inspection respectively, is the process of using non-invasive means to inspect a component or structure to detect cracking, corrosion, or other defects within the material.Offshore oil rigs will sit in the water, braving the elements, salt corrosion, and marine growth for 20-30 years. To ensure that these structures and other water-based assets remain safe, there are regulations that govern their Inspection, Maintenance, and Repair (IMR). Disasters such as what happened to the<a href="https://www.offshore-technology.com/features/feature-the-worlds-deadliest-offshore-oil-rig-disasters-4149812/" rel="noreferrer noopener nofollow" target="_blank">&nbsp;Alexander L Kiellande oil platform in 1980</a> or more recent <a href="https://www.cbsnews.com/news/gulf-of-mexico-fire-ocean-burst-pipeline" rel="noreferrer noopener nofollow" target="_blank">near misses in the Gulf of Mexico</a> have been caused by cracking and corrosion of subsea structures left unchecked.Manipulators and human divers routinely carry out inspections of structures for cracking or corrosion using<a href="https://en.wikipedia.org/wiki/Ultrasonic_thickness_measurement" rel="noreferrer noopener nofollow" target="_blank">&nbsp;Ultrasonic Thickness</a> (UT),<a href="https://en.wikipedia.org/wiki/Cathodic_protection" rel="noreferrer noopener nofollow" target="_blank">&nbsp;Cathodic Protection</a> (CP), or<a href="https://en.wikipedia.org/wiki/Alternating_current_field_measurement" rel="noreferrer noopener nofollow" target="_blank">&nbsp;Alternating Current Field Measurement</a> instruments. ROV manipulators that are dexterous, more compact, and have advanced software control (including being able to precisely control the position and orientation of the instrument) have enabled small ROVs to <a href="https://blueprintlab.com/blog/degrees-of-freedom-vs-functions-of-a-robotic-arm/" target="_blank">carry out these tasks completely remotely</a>. Companies such as Fugro are<a href="https://www.fugro.com/about-fugro/our-expertise/remote-and-autonomous-solutions/remote-and-autonomous-vessels" rel="noreferrer noopener nofollow" target="_blank">&nbsp;pioneering remote operations</a> where an Unmanned Surface Vehicle (USV) hosting an ROV can deploy and inspect infrastructure using dexterous manipulators.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ4NzE2Njk5OTc0LXBhc3RlZCBpbWFnZSAwLnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><h2 id="isPasted">2. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Dexterous (Human-Like) Intervention&nbsp;</h2>Achieving the same (or better) level of dexterity as a human is the holy grail of dexterous robotic manipulation. Huge progress has been made in recent years in terms of the size and joint dexterity of robotic manipulators above and below the water. One current limitation is the ability to achieve precise, small-scale dexterity. Land robots have demonstrated the use of robotic hands with fingers; successfully manufacturing similar technologies underwater is far more difficult and yet to be commercially solved.Some dexterous tasks such as tying a knot, attaching a carabiner, or fastening a nut to a bolt have all been demonstrated using underwater manipulator technology. This has allowed industries to use robotic manipulators for net repair in aquaculture settings, and conduct complex military tasks.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ4NzE2NzM2MTM1LUFscGhhLTUtQ2xpcHBpbmctQ2FyYWJpbmVyLTc2OHg1NzAuanBnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib">Alpha 5 Manipulator attaching a carabiner underwater&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ4NzE2Nzg0NjE3LXBhc3RlZCBpbWFnZSAwICgxKS5wbmciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib"><h2 id="isPasted">3. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Construction And Repair</h2>With hydraulic and electric actuators able to exceed the capability of humans, underwater manipulator arms are used for moving large tools and instruments around to aid in the construction, maintenance, repair, and decommissioning of a whole range of subsea infrastructure. In the offshore energy industry, manipulators move large hooks attached to cables for deployment and recovery of subsea infrastructure and wield torque tools or welding torches.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ4NzE2ODE1NTExLU1pY3JvLUlQLUNhbWVyYS1CYW5uZXItMi03Njh4NDMyLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><h2 id="isPasted">4. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Close Visual Inspection</h2>Like NDT, Close Visual Inspection (CVI) is concerned with looking at infrastructure with <a href="https://blueprintlab.com/products/underwater-rov-camera/" target="_blank">HD subsea cameras</a> to detect any issues that need repair or follow up. Manipulators with good reach (length) and dexterity enable CVI in hard-to-reach areas such as inside pipe inlets and behind propellers.This ability for confined space access is a value-add offered by more modern, compact, electric manipulators like Blueprint Lab&rsquo;s Reach Alpha and Reach Bravo. Leveraging HD CVI allows for Underwater Inspection in Lieu of Dry-docking (UWILD). UWILD, as the name suggests, is the CVI/NDT of a ship&rsquo;s hull that avoids needing to take the vessel out of the water; a huge cost and efficiency saving.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ4NzE2ODQ1NDc1LUJyYXZvLVdyaXN0LUNhbWVyYS03Njh4NDI4LnBuZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 766px;" class="fr-fic fr-dib"><h2 id="isPasted">5. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Cleaning/Anti-Fouling&nbsp;</h2>Over time, subsea infrastructure can become coated in marine growth (barnacles etc) and other biofouling substances. To properly inspect the condition of the infrastructure (using NDT or CVI methods), surfaces must be cleaned of any marine growth. This is generally done by using high-power water pressure, a cavitation blaster, or a rotary brush.In some scenarios, this will be done using a fixed system on the ROV. In other cases, the dexterity of a manipulator is required or beneficial to adequately reach all areas that need to be inspected. This is especially relevant where the geometry of the inspection area is more complex, such as at the weld nodes of a jack-up rig.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ4NzE2ODc1MDg5LU9pbF9SaWctNzY4eDU3Ni5qcGVnIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib">Subsea steel joints&nbsp;<h2 id="isPasted">6. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Sea Mine And UIED Intervention&nbsp;</h2>Military clearance divers carry out dangerous tasks including deploying a shaped charge to disarm a mine or examining and disrupting a Waterborne Improvised Explosive Device (WBIED). These tasks are still done by humans because they require high fidelity perception and dexterous intervention capabilities not previously available through a remote solution. Recently, with the release of more dexterous, compact manipulator arms like the Reach Alpha, military organisations are investigating ways for ROVs to start to do some of these more dangerous tasks.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ4NzE2OTEzMTM1LTEwMDU1MzczMDc1XzIxNmRkZTc3NWFfYy5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib">Image Source: Flickr<h2 id="isPasted">7. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Special Recovery Operations (e.g. Downed Aircraft, Drowning Victims)</h2>Special Recovery Operations include scenarios such as recovering a downed aircraft from the seafloor or drowning victims from a lakebed. These sensitive tasks have historically been conducted by highly skilled military or civilian diver teams. Recently ROVs have been able to assist and in some cases take-over, these high-risk tasks.Dexterous manipulators can be used to tie knots or attach carabiners to recover objects or for the recovery of forensic items without disturbing the lake/sea bed.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ4NzE2OTYxMjYwLUhFQVJULXNpbXVsYXRpb24tNzY4eDQ4OS5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 766px;" class="fr-fic fr-dib">Alpha Grabber during a simulated recovery mission &ndash; See the full video story below!&nbsp;<iframe src="https://www.youtube.com/embed/19V9YdC-ZOM?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" style="width: 768px; height: 430px;"></iframe><h2 id="isPasted">8. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Oceanography And Hydrography (Sampling And Measurement)</h2>Understanding the condition of our marine environment is critical for building a global picture of the Earth&rsquo;s ecosystem. Scientists regularly take samples from the sea bed for analysis and collect marine organisms for biological study. In some cases, sampling and organism collection requires precise positioning of a sampling device as well as the ability to retrieve a sample without stirring up sediment from the seafloor. Additionally, measuring devices (rulers and callipers) are often used to properly characterize an object of interest. In these cases, a dexterous manipulator allows for the ROV to sit on the seafloor and for confined areas to be reached (such as amongst a coral reef)<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1648717362455-EGM_5604_Credit_AIMS-EricMatson-2048x1367.jpeg" style="width: 766px;" class="fr-fic fr-dib">Image source: Scimex<h2 id="isPasted">9. <style type="text/css" id="isPasted"></style><style type="text/css"></style>Autonomy And Custom Control&nbsp;</h2>Robotics and Autonomous Systems researchers around the world are pioneering the use of underwater robots in a variety of autonomous applications. Some examples of this are using manipulators to autonomously interact with a subsea control panel or using multiple robots to lift, carry, and place an object, thereby utilising the lift capacity of more than one underwater vehicle.<h2 id="isPasted"><style type="text/css" id="isPasted"></style><style type="text/css"></style>Final Thoughts </h2>The uses of underwater ROV manipulators are varied and constantly expanding. As a company, Blueprint Lab is seeking not just to make incredible robotic arms, but to actually solve industry problems. We constantly discuss and explore the problems that our clients are trying to solve and have multiple projects in work regarding underwater manipulation, perception and control.

The aim of this article is to provide a high-level answer to the question: “What do people use underwater robotic arms for?” If you’ve worked with Remotely Operated Vehicles (ROVs) before, this article probably isn’t for you. For everyone else, let’s go.

Top Uses of Underwater ROV Manipulators

A Quick Start Guide to Underwater ROVs. In this guide, you’ll learn about what defines a remotely operated vehicle, different types of ROVs, and what they are used for. Underwater ROVs are used to observe and interact underwater across a range of industries.

What are underwater ROVs & What can they be used for?

Is there life on Jupiter&#39;s moon Europa? An ocean suspected to be under miles of ice gives science hope. But how could it be reached and explored? Researchers at the DFKI Robotics Innovation Center have been investigating this question since 2012 in the Europa Explorer project series. The focus is on the development of robotic systems that can penetrate the water, explore it autonomously and remain there for a longer period of time. At the end of the third phase of the project, the autonomous underwater robot DeepLeng will now be put to the test in a frozen lake in northern Sweden.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1647686785744-csm_Deep_Leng-9963_b8f4a16cf7.jpg" style="width: 766px;" class="fr-fic fr-dib">DeepLeng in the Maritime Exploration Hall of the DFKI in Bremen &copy; DFKI, Annemarie PoppAn average of 600 million kilometers separates the earth from the icy moon Europa, one of the four large moons of Jupiter. Underneath its mighty shell of water ice an ocean is assumed about 100 km deep with hydrothermal vents at its bottom, which release hot and mineral-rich water into their surroundings, creating the basis for living organisms. As part of the German Aerospace Center&#39;s (DLR) Explorer Initiatives, the Robotics Innovation Center has been investigating how this highly interesting place for science could be explored. To this end, the researchers developed autonomous underwater vehicles (AUVs), which can navigate and explore its surroundings under an ice sheet autonomously, in three successive phases of the project. In the third phase of the Europa Explorer project for long-range under-ice navigation (EurEx-LUNa), the final field tests are ahead, in which the AUV DeepLeng will be tested for the first time outside the laboratory under realistic conditions: For this purpose, five DFKI scientists will travel to the small northern Swedish town of Abisko in the national park of the same name on Lake Tornetr&auml;sk from March 20 to April 2, 2022. Here, north of the Arctic Circle, with outside temperatures expected to be around minus 10 degrees, the underwater robot is to autonomously explore the frozen lake, which is up to 168 meters deep. Despite the freezing cold, it is a baptism of fire for the researchers, who are housed in a research station in Abisko for the duration of the field trials, to prove the feasibility of the concept for autonomous under-ice navigation. Once launched by the mobile crane, the hole in the ice allows only a brief glimpse of the three-meter-long system with its eye-catching yellow cover before it dives down and disappears completely under the ice shell. Here, the robot has to find its way around completely on its own in murky conditions, gather as much information as possible from its surroundings and then navigate back to the docking station, where it can transmit the data, it has collected and recharge its batteries.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1647686861679-csm_auv_detaches_from_dockingport_3771a69fbc.png" style="width: 766px;" class="fr-fic fr-dib">Animation of autonomous docking under ice. &copy; DFKI, Meltem FischerFor the success of this challenging mission, the researchers further developed both the AUV&#39;s hardware and software in the EurEx-LUNa project. Among other things, they equipped DeepLeng with an USBL underwater navigation system that can transmit, receive, and process acoustic signals. They also used machine learning to train the system to find its way even under the most adverse conditions and to dock safely at the docking interface. Now, the preliminary work in the project, as well as in the entire Europa Explorer project series, should pay off in the field tests in Sweden. As a continuation of the Europa Explorer and EurEx-SiLaNa projects, EurEx-LUNa is funded since March 1, 2020, until May 31, 2022, by the German Federal Ministry of Economics and Climate Protection (BMWK) via the German Aerospace Center (DLR). Note: For those who want to get a picture of the field trials in Sweden, a live camera will be installed on site. The images will be broadcast via YouTube. There will also be a field test blog where project leader Dr. Marc Hildebrandt will report daily on what has happened over the past day. The links to the live stream and the blog will be announced here in the next few days. More information: Project EurEx-LUNa: <a href="https://robotik.dfki-bremen.de/en/research/projects/eurex-luna/" rel="noreferrer" target="_blank">https://robotik.dfki-bremen.de/en/research/projects/eurex-luna/</a> System DeepLeng: <a href="https://robotik.dfki-bremen.de/en/research/robot-systems/deepleng/" rel="noreferrer" target="_blank">https://robotik.dfki-bremen.de/en/research/robot-systems/deepleng/</a> &nbsp;

The predecessor version of DeepLeng dives autonomously in the icy Stadtwaldsee in Bremen, Germany.  © DFKI, Annemarie Popp

Is there life on Jupiter's moon Europa? An ocean suspected to be under miles of ice gives science hope. But how could it be reached and explored? Researchers at the DFKI Robotics Innovation Center have been investigating this question since 2012 in the Europa Explorer project series.

On an icy mission: DFKI researchers test extraterrestrial under-ice navigation in northern Swedish National Park

Our seas and oceans currently contain somewhere between 26 and 66 million tonnes of plastic waste, most of which is lying on the seafloor. This represents an enormous threat to marine plants and animals and to the ecological balance of the seas.But removing waste from the waters is a complex and expensive process. It is often dangerous, too, because the work is generally done by scuba divers. The cleanup operations are also usually limited to the water surface. In the <a href="https://seaclear-project.eu/" rel="noreferrer" target="_blank">SeaClear Project</a>, a team at TUM is working with eight European partner institutions to develop a robotic system capable of collecting underwater litter. &nbsp;<h2>Four robots working together</h2>The system combines four robotic components: an autonomous surface vehicle performs an initial scan of the sea bottom and localizes large litter pockets. Next an observation robot is lowered into the water to detect undersea litter and transmit additional information to the computers such as close-up images of the sea bottom.In clear water and with good visibility, an aerial drone is also used to identify further litter objects. The resulting data are combined to generate a virtual map. A collection robot then visits defined points on the map and picks up litter. It uses a gripper to place larger pieces in a basket that is towed to shore by the autonomous boat.<div class="fr-img-space-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1641200382603-Seaclear_Foto.jpg" style="width: 766px;" class="fr-fic fr-dib">A system consisting of four robots ensures clean sea floors. Image: The SeaClear Project&nbsp;</div><h2 id="isPasted">The challenge of currents</h2>“Developing autonomous robots for underwater applications is a unique challenge” says Dr. Stefan Sosnowski, the technical director of the SeaClear project at the Chair of Information-oriented Control at TUM. That is because, in contrast to land-based applications, very special conditions prevail in the water. “When a piece of litter is identified and located, the robot needs to get close to it. To do so, it may need to overcome strong currents. The task of TUM in the SeaClear project is to enable the robot to move in the right direction.”<h2>Efficient machine learning</h2>To achieve this, the team is using machine learning methods. An artificial intelligence (AI) module performs calculations and learns the conditions under which the robot will move in certain ways. This makes it possible to predict its behavior precisely.“Another challenge is that we don’t have the computing power at our disposal that we would on dry land,” says Prof. Sandra Hirche, director of the chair and SeaClear principal investigator. “We do not have links to large data centers with supercomputers. So we need highly efficient algorithms that run with limited resources. We are therefore working with high-efficiency sampling methods that arrive at precise predictions with minimal data. The AI system simply discards unnecessary information.”<h2>90% success rate</h2>When the SeaClear system is fully operational, it is expected to achieve 80% accuracy in classifying underwater litter and to successfully collect 90% of it. This is comparable to the results produced by scuba divers. The initial trials with the prototype were carried out in October 2021 in Dubrovnik, Croatia, where the water is clear and visibility is excellent. Further trials are scheduled in the port of Hamburg in May 2022.<div class="fr-img-space-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1641200417136-First_Litter_Grabbed_1.jpeg" style="width: 766px;" class="fr-fic fr-dib">The research group of the SeaClear project observes the underwater activities of the robot on the monitor. Image: The SeaClear Project&nbsp;</div><hr><h3 id="isPasted">Publications:</h3>P. Bevanda, S. Sosnowski, S. Hirche, "Koopman operator dynamical models: Learning, analysis and control", Annual Reviews in Control , 2021, 52, 197-212 ,&nbsp;<a href="https://www.sciencedirect.com/science/article/abs/pii/S1367578821000729?via%3Dihub" rel="noreferrer" target="_blank">DOI:10.1016/j.arcontrol.2021.09.002</a>

The robot of the SeaClear Project is able to detect and collect underwater litter. Image: The SeaClear Project

Removing litter from oceans and seas is a costly and time-consuming process. As part of a European cooperative project, a team at the Technical University of Munich (TUM) is developing a robotic system that uses machine learning methods to locate and collect waste under water.

Robots collect underwater litter

Autonomous Underwater Vehicles (AUVs) play a vital role in fields such as hydrocarbon drilling and extraction, marine surveying and aquatic environmental monitoring. An AUV can perform functions in which it is difficult for divers to accomplish, and can descend to depths which would put human operators in danger.Most AUV products on the market today are large, capable of carrying heavy payloads, and fitted with a large battery to enable them to stay underwater for long periods of time. This type of product suits customers such as oil companies, which can afford the substantial cost not only to buy a large AUV, but to transport it to where it is needed, to manoeuvre it into position, and to operate it.UK-based marine products supplier <a href="https://planet-ocean.co.uk/wp/" rel="noopener" target="_blank">Planet Ocean</a> spotted that this left a gap in the market for a smaller, more affordable AUV. This realization spurred the development of <a href="https://planet-ocean.co.uk/wp/?page_id=4509" rel="noopener" target="_blank">ecoSUB</a>, a range of small, low-cost AUVs which can be easily carried, launched, operated and retrieved from the water by a single person.Its goal was to democratize the use of AUVs: to bring them within reach of all research institutes, universities, commercial users, users in less developed countries, and of other users who have limited resources.&nbsp;It turned out that the design of this innovative AUV required a motion tracking sensor which was both compact and accurate.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1619774171204-1619774171204.png" alt="Capture 2" width="1289" srcset="https://www.xsens.com/hs-fs/hubfs/Capture%202.png?width=645&amp;name=Capture%202.png 645w, https://www.xsens.com/hs-fs/hubfs/Capture%202.png?width=1289&amp;name=Capture%202.png 1289w, https://www.xsens.com/hs-fs/hubfs/Capture%202.png?width=1934&amp;name=Capture%202.png 1934w, https://www.xsens.com/hs-fs/hubfs/Capture%202.png?width=2578&amp;name=Capture%202.png 2578w, https://www.xsens.com/hs-fs/hubfs/Capture%202.png?width=3223&amp;name=Capture%202.png 3223w, https://www.xsens.com/hs-fs/hubfs/Capture%202.png?width=3867&amp;name=Capture%202.png 3867w" sizes="(max-width: 1289px) 100vw, 1289px" class="fr-fic fr-dii" style="width: 777px;">Xsens makes accurate underwater navigation possibleThe efficient operation of the ecoSUB AUV calls for accurate location data derived by the dead reckoning technique. On the surface of the water, geolocation is easy: satellite positioning signals determine position to a typical accuracy of ±5m.The satellites’ RF signals do not penetrate water, however, so the ecoSUB AUV determines its position by continuously tracking its motion relative to its launch point on the surface.&nbsp;For this motion tracking function, ecoSUB uses the <a href="https://www.xsens.com/inertial-sensor-modules" rel="noopener" target="_blank">Xsens MTi-3 AHRS</a> (Attitude and Heading Reference System), together with a discrete pressure sensor for depth measurement. The MTi-3 sensor provides the ecoSUB with highly accurate measurements of roll, pitch, heading and acceleration. The ecoSUB’s on-board computer continuously converts these measurements into position coordinates.<iframe src="https://www.youtube.com/embed/7EEqPm0ylWk?&amp;t=6s&amp;wmode=opaque&amp;rel=0" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 788px; height: 501px;"></iframe>The especially challenging requirements of designing a small and light AUV made the Xsens motion tracking sensor the ideal fit.&nbsp;‘The fundamental design objective for the ecoSUB was to make an AUV that was small and light enough for an average person to lift, while still having enough load-carrying capacity and range to perform useful tasks. Our design for the ecoSUB fits an “A” size sonar buoy tube – it is 1m long, and weighs just 4kg. To optimize the ecoSUB’s range and dynamic characteristics, we needed to apportion as much of the internal space as possible to the battery and the motor. So the motion sensor and the rest of the control electronics system have to be packed in a small space, in the presence of the strong magnetic fields generated by the motor system. And of course the accuracy of the AUV’s position data is absolutely crucial. When the AUV is being used for instance to detect an oil leak or to monitor variations in the oxygen content of sea water, users need to know exactly where in three dimensions it has taken its measurements.’Jeremy Sitbon, ecoSUB Chief Robotics EngineerXsens MTi-3 motion tracker: Small, light, reliableThe constraints applying to the design of the ecoSUB meant the motion sensor had to offer three essential characteristics:<ul><li>High accuracy in the sensor’s motion tracking data&nbsp;</li><li>Dependability, with high immunity to magnetic interference</li><li>Small size and weight</li></ul>The Xsens MTi-3 AHRS delivers on all three counts. The MTi-3 integrates multiple sensor functions including 3D accelerometer, gyroscope and magnetometer plus a processor.The accuracy of the sensor’s static measurements of roll and pitch is ±0.5°, and for yaw the value is ±2°. In use, the ecoSUB typically achieves positioning accuracy of ±5% of the distance travelled when using only the MTi-3 motion sensor and the pressure sensor measurements.The accuracy of the sensor’s measurements remains stable regardless of changes in the magnetic field around it. The ecoSUB designers have made full use of the sophisticated filtering capabilities built into the MTi-3 sensor: the sensor can be configured for operation in various types of operating environments, including for continuous strong magnetic interference. This is ideal for the ecoSUB, in which the propellers are coupled to the motor magnetically.All functionality is squeezed into a compact package which measures just 12.1 x 12.1 x 2.55mm and weighs less than 1g. Typical power consumption is less than 100mW, helping the ecoSUB’s battery to last longer and extend the vehicle’s range.Opening up the use of AUVs to whole new market segmentsAfter completing sea trials, the innovative ecoSUB AUV went into full commercial production in 2020. Jeremy Sitbon says that Planet Ocean is excited about the possibility of introducing a new generation of users to the utility of AUVs. The ecoSUB’s capabilities include acoustic (sonar) communication, enabling multiple ecoSUB AUVs to be used concurrently in ‘shoals’ to give a 3D picture of subsea conditions. The ecoSUB can act like a marine ‘truck’ – a carrier for almost any type of sensor or other payload, so the potential for its use is almost limitless.<blockquote>‘The success of the product comes down to our ability to pack a lot of functionality and performance into a very small space. Our decision to use the MTi-3 played a really important part in our ability to make this design successful. I’m very happy that we made the right choice!’</blockquote>Jeremy Sitbon, ecoSUB Chief Robotics Engineer&nbsp;Learn more about the <a href="https://www.xsens.com/mti-3" rel="noopener" target="_blank">Xsens MTi-3 AHRS</a>&nbsp;here.Choosing your productWant to know the right inertial measurement unit for your application? Try our recommendation tool and find out what MTi you need by answering just 3 questions.<a href="https://www.xsens.com/cs/c/?cta_guid=e67ae0db-e496-4b1b-aaae-0f33c66a97bb&signature=AAH58kERCATymf5UB4b7WHUo8PJHsSLMlQ&pageId=42748316968&placement_guid=0e0cf390-8244-48ac-aa9c-cc22448b3988&click=38fa5093-baba-426c-92e2-244e329bd831&hsutk=26cd9f0233255f079c3a3909dd662892&canon=https%3A%2F%2Fwww.xsens.com%2Fcases%2Fsmall-light-and-accurate-xsens-mti-3-sensor-helps-planet-ocean-open-up-new-markets-for-autonomous-underwater-vehicles&utm_referrer=https%3A%2F%2Fwww.xsens.com%2Fexplore%3Ffilter%3Dcases&portal_id=3446270&redirect_url=APefjpHFi12gvYuHqoWSZfHrIGqiyim6_ONHhAlUSf5P2fSu9LX3yPDWqIEBNMTq7zPbzoK-WfoIZg8Bfa15xkMpbz1GkbkzFFTzUwGCgcPUASxo3Mq8GkOyNHKblRAbv48KApkSyYPNJwvTLiTVMI_w5QhewNpuAjHGGtTfSn2xG8nR_UcoJBph_ito-8xtKFpTW9QoAoROG3GmG8mI-y8TDzizVxJguxXZRuSkE0Jr3QNx52alDInkfDxEm_QGTqfCxOEdsmfaCQUt-NiFKNTC_MtmiftGKw&__hstc=81749512.26cd9f0233255f079c3a3909dd662892.1612181589013.1619708666522.1619773674521.185&__hssc=81749512.8.1619773674521&__hsfp=1627031933&contentType=blog-post" target="_blank" title="Recommendation tool">Recommendation tool</a>&nbsp;

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Xsens AHRS Enables Planet Ocean To Open Up New Markets For Autonomous Underwater Vehicles

In this episode, we talk about Charm Industrial’s novel approach for carbon offsetting, a concept fitness drone from Hongik University that could be the first to commercialize, and a joint effort between MIT and the US Navy to understand how sound waves are altered by water conditions in the North Pole. As always, you can find these and other interesting &amp; impactful engineering articles on Wevolver.com.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/e71ade31-1622-42a8-93a9-a489df82c655?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe><h3>EPISODE NOTES</h3>(0:50) -&nbsp;<a href="https://www.wevolver.com/article/a-charm-ing-approach-for-carbon-offsetting" target="_blank">A Charming Response To The Carbon Offsetting Controversy</a>:&nbsp;Approximately 85% of all carbon offsetting efforts do not actually remove any additional carbon dioxide from the atmosphere and Charm wants to change that by injecting bio oil into wells that stored crude oil at one point.(8:10) -&nbsp;<a href="https://www.wevolver.com/article/drones-as-fitness-trainers" target="_blank">Drones As Personal Fitness Instructors</a><a href="https://www.wevolver.com/article/organic-material-may-help-design-energy-efficient-heating-and-cooling-systems" target="_blank">:</a>Drones are finally making their debut in the fitness scene with a concept design from Hongik University that could serve as the first commercially viable fitness drone and pave the way for the future of the industry.&nbsp;(14:20) - MIT &amp; ONR’s Trip To The North Pole:Acoustic signals get distorted in regions of the ocean where warm water meets cold water - especially in the Beaufort Sea - so MIT has collaborated with ONR to understand these distortions in hopes of allowing exploration in these regions without risking loss of communication.--About the podcast:Every day, some of the most innovative universities, companies, and individual technology developers share their knowledge on Wevolver. To ensure we can also provide this knowledge for the growing group of podcast listeners, we started a collaboration with two young engineers, Daniel Scott Mitchell &amp; Farbod Moghaddam who discuss the most interesting content in this podcast series.&nbsp;To learn more about this show, please visit the&nbsp;<a href="https://www.wevolver.com/profile/the.next.byte" target="_blank">shows page</a>. By following the page, you will get automatic updates by email when a new show is published.Be sure to give us a follow and review on <a href="https://podcasts.apple.com/nl/podcast/the-next-byte/id1548255861?l=en" rel="nofollow" target="_blank">Apple</a> podcasts, <a href="https://open.spotify.com/show/6lPPsRtegnivsRUEsQ09R7?si=IPMiah7xT_apJtPjqvXMlA" rel="nofollow" target="_blank">Spotify</a>, and most of your favorite podcast platforms!

In this episode, we talk about Charm Industrial’s novel approach for carbon offsetting, a concept fitness drone from Hongik University that could be the first to commercialize, and a joint effort between MIT and US Navy to understand how sound waves are altered by water conditions in the North Pole.

Podcast: Charm's Carbon Offsets, Fitness Trainer Drones, MIT Studies Sound Waves In The North Pole

The deployment of divers to make underwater video recordings is difficult and expensive. It calls for professionals who are trained in two disciplines: diving and video camera operation. There are even some video inspection tasks – such as recording pictures of the inside of an undersea pipe – which are impossible for divers because the location is inaccessible to a person, or too dangerous.Now a Russian manufacturer, <a href="https://gnomrov.com/" rel="noopener" target="_blank">Underwater Robotics</a>, has developed a Remotely Operated underwater Vehicle (ROV) which can carry out video photography missions under the control of an operator who remains safe and dry on the surface of the water. Underwater Robotics’ GNOM-PRO, the world’s smallest and lightest ROV designed for video recording missions, enables users to perform underwater visual inspections without the need for a diver. It also provides a safe way to view small or hazardous locations underwater.Offering outstanding underwater dynamic characteristics, its motion is controlled simply with a joystick. And the key to its stability and ease of use is a <a href="https://www.xsens.com/inertial-sensor-modules" rel="noopener" target="_blank">3D motion sensor</a> from Xsens.Complete motion-tracking module speeds development of ROVXsens’ MTi-3 is a complete AHRS (Attitude and Heading Reference System) including gyroscopes, accelerometers and magnetometer in a 12.1 x 12.1 mm module. It includes Xsens’ industry-leading sensor fusion algorithm, which maintains high accuracy over the sensor’s lifetime, and performs sensor auto-calibration. The use of an integrated Xsens module enabled Underwater Robotics to develop the motion control system in the GNOM-PRO quickly. The module’s calculated measurements of roll, pitch and heading are also easy to integrate into the GNOM-PRO’s control software.When choosing the motion sensor for the GNOM-PRO, Underwater Robotics also carefully considered its size and weight. An important feature of the ROV is that it can be carried by hand: the complete system including the ROV and its maximum 400m-long tether fits in two portable cases. The ROV itself measures 520 x 440 m x 347 mm and weighs 25 kg: this means that it can easily be transported to the site of a mission, and launched and operated from almost any type of boat. Its compact size also means that it can be used in constricted spaces such as pipelines in which a conventional ROV will not fit.The MTi-3 sensor’s small size and its light weight, less than 1g, were therefore highly attractive. But Underwater Robotics’ choice of the MTi-3 was as much about the sensor’s dynamic characteristics. The GNOM-PRO is intended for use in monitoring and maintenance of marine and underwater installations such as oil production platforms and hydroelectric generation plants, for the inspection of ships’ hulls, and for monitoring functions in hazardous locations such as nuclear power plants. Its use as a video camera platform calls for high dynamic stability to ensure that video images are not impaired by blur, shake or other image artefacts.Maintaining stability in waterThe GNOM-PRO’s small size and light weight, however, mean that it is more strongly affected by the motion of waves and currents than a larger vehicle is. The MTi-3’s high performance, including roll and pitch accuracy of ±0.5° under static conditions (±0.8° under dynamic conditions), enables the operator to maintain stable orientation. The GNOM-PRO also has an Auto-Heading Mode to enable the operator to set its direction of travel via an automatic setting controlled by the heading output from the MTi-3. In addition, the MTi-3 sensor’s measurements of velocity, roll, pitch and yaw enable accurate dead reckoning from a known starting position, to establish the geolocation of the ROV.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1618320084977-1618320084977.png" alt="352" width="814" srcset="https://www.xsens.com/hs-fs/hubfs/352.jpg?width=407&amp;name=352.jpg 407w, https://www.xsens.com/hs-fs/hubfs/352.jpg?width=814&amp;name=352.jpg 814w, https://www.xsens.com/hs-fs/hubfs/352.jpg?width=1221&amp;name=352.jpg 1221w, https://www.xsens.com/hs-fs/hubfs/352.jpg?width=1628&amp;name=352.jpg 1628w, https://www.xsens.com/hs-fs/hubfs/352.jpg?width=2035&amp;name=352.jpg 2035w, https://www.xsens.com/hs-fs/hubfs/352.jpg?width=2442&amp;name=352.jpg 2442w" sizes="(max-width: 814px) 100vw, 814px" class="fr-fic fr-dii">Underwater Robotics decided to embed the MTi-3 in the GNOM-PRO ROV after exhaustive evaluation of the motion sensor market.&nbsp;‘On every parameter which we considered important, our evaluation pointed us towards the MTi motion tracker. It is a full-function motion tracker including sensor fusion software, but Xsens fits all the functionality into a small and light package, which is very important for a portable product such as the GNOM-PRO. But the small size does not compromise performance – the accuracy of the MTi-3’s measurements are very good, and in conjunction with the depth measurements provided by a separate pressure sensor, allows the user to tag each frame of video with an exact geolocation.The performance of the GNOM-PRO ROV with the MTi-3 sensor has brought us great success – the product is now in use around the world in countries including France, Italy, Germany, Spain, the US and India as well as Russia. That is why I am sure that we made the right decision to use the MTi-3.’Boris Rozman, CEO of Underwater RoboticsLearn more about the Xsens MTi-3 AHRS&nbsp;The MTi-3 stands out for its small form factor (12.1mm x 12.1mm), easy integration, low cost and robustness – as well as its strapdown integration algorithm.Want to know more? Go to the <a href="https://www.xsens.com/mti-3" rel="noopener noreferrer" target="_blank">MTi-3 page</a>.

autonomous underwater vehicles (AUVs)

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