SiC v GaN v SJ MOSFETs v IGBTs? Each has its place and that’s why we, at Power Integrations, do not treat GaN as a market, it’s a technology. It’s just one of many in our armoury, along with SiC and various different MOSFET technologies and we use what we determine to be the most appropriate, application by application.The perception of GaN’s place has changed significantly with our recent, dramatic – and I think that is a justifiable adjective to use – launch of a GaN device with a breakdown voltage of 1700 V. Let’s put that into perspective: 1700 V is 450 V higher than our previous best, and 70% higher than the best offered by any other maker (which, incidentally, we believe is currently not available as a shippable high-volume product). Most GaN companies are struggling to get much above 750 V. We launched a flyback power supply IC, InnoMux™-2, that is rated at 1700 V, so can easily cope with 1000 VDC rail applications. It is available to order with 16 weeks delivery leadtime in volume, and samples are available off the shelf.&nbsp;What does this mean for industry and the whole ‘GaN v SiC, which power IC technology is best’ discussion?&nbsp;In short, we believe that GaN will soon be able to address all application sectors from the low 10s of watts up to 100s to kilowatts.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1737125810639-gan2.jpg" style="width: 100%px;" class="fr-fic fr-dib">Let’s break it down. GaN has already won the low power charger market from 30 W to, say, 240 W. This is because it is much more efficient than super junction MOSFETs, featuring negligible switching losses and very low specific RDSON. Therefore, higher power densities are achievable, devices can be made smaller or more powerful, and the thermal management challenge is much reduced. &nbsp;And although MOSFETs are currently cheaper than GaN HEMTs, the need for advanced, resonant topologies and heatsinks makes them less cost effective than GaN at the system level. This GaN advantage will only improve as economies of scale kick in and production ramps up. The only reason why MOSFETs may be preferred for very low power applications (for example &lt;20 W) is that the GaN die at low power levels are so small they are hard to handle.&nbsp;As we move up in power levels through 500 W, 1 kW and up to 10kW, GaN is also winning. Here we are looking at applications such as refrigerators, e-bike chargers, washing machines and other white goods, HVAC compressors, solar, certain automotive functions such as the on-board charger and lead-acid replacement battery circuits, and server PSUs. All these are transitioning from MOSFETs. Some have already made the move to SiC, and since SiC and GaN have comparable efficiency ratings, why should GaN prevail here? Simply, the reason is cost. SiC requires huge amounts of energy to create the high processing temperatures required. GaN does not. A GaN device is inherently no more expensive to produce than a silicon part – devices can even me made on the same production lines with relatively few modifications.&nbsp;More and more of these 1 to 10kW applications – previously the preserve of MOSFETs and SiC - will be addressable by GaN, and it won’t stop there. Currently, GaN tops out at around 7-10 kW. That’s a little short of satisfying the needs of the EV inverter market – the biggest single power IC application TAM – but you only need another factor of 10 to get to EV power levels of a few 100 kW, and a factor of 10 in high tech is a matter of just a few years. There's no substantive constraint, there's no physical limitation…it’s not invention or inspiration that is needed, it's development.&nbsp;At the very high power end of the scale - multi-megawatt wind turbines and gigawatt high-voltage DC installations - IGBTs are well-established and comparatively cheap. Therefore, SiC looks set to be squeezed into a relatively small section of the market, which needs the higher currents that the vertical technology can offer.One final point. When any new technology comes along, or takes a significant step forward, the first thing it does is directly replace the previous tech. But then someone bright comes along and says, ‘well that’s OK, but the new tech allows us to completely rethink the design – to come up with a new concept that makes best use of the new technology without referring back to what was required by the old’. We’re continuing to innovate at the microelectronics, packaging, system, and algorithm levels to develop application-specific power products that roll the rock forward in efficiency, cost effectiveness and component count, opening up new ideas for new markets.&nbsp;

SiC v GaN v SJ MOSFETs v IGBTs? Each has its place.

Where GaN can, it should, and GaN can in more and more places

Wevolver met with &nbsp;Petter Myhre, Product Marketing Director at Nordic Semiconductor at CES 2025 to discuss the latest advancements in semiconductor technology. &nbsp;In the folowing interview Myhre introduces the nRF54L Series, Nordic Semiconductor’s recent groundbreaking release, which marks a significant progression from the widely utilized 52 Series in Bluetooth Low Energy designs.<h2>Interview with Petter Myhre, Product Marketing Director at Nordic Semiconductor at CES 2025</h2>Wevolver: Can you please introduce yourself and tell us a bit about the nRF54L Series that you've launched and what makes it so special?Petter Myhre: Certainly. I'm Petter Myhre, Product Marketing Director at Nordic Semiconductor. The nRF54L Series, our recent launch, advances our popular 52 Series, which has been a leading solution for Bluetooth Low Energy designs for over a decade. This new series increases our market share to 40% in Bluetooth Low Energy by featuring a completely new ultra-low power radio and enhanced MCU functionality. It includes an ARM Cortex M33 processor running at 128 MHz and offers up to 1.5 MB non-volatile memory.Wevolver: That's exciting. Could you elaborate on the improvements introduced with the new radio?Petter Myhre: Absolutely. The new radio significantly reduces power consumption—demonstrated to be about two-thirds that of the 52 Series. It boosts output power to 8dBm and improves sensitivity to minus 96dBm on the receive side. Additionally, it's equipped with Bluetooth 6, supports fine-grained ranging between devices through a new channel-sounding feature, and is compatible with multiple protocols including Thread, Matter, and Zigbee.Wevolver: With CES focusing on smart homes this year, how does the Series fit into smart home applications and other current trends?Petter Myhre: The nRF54L Series supports Matter, making it highly relevant for smart home technologies. It's a versatile wireless microcontroller suitable for any battery-powered, low power consumption product requiring advanced wireless capabilities.Wevolver: How does Nordic support developers who are looking to explore or develop with the nRF54L Series?Petter Myhre: Nordic is deeply committed to supporting developers. For the nRF54L Series, we provide extensive technical support, free hardware reviews, and antenna tuning. Development kits are available through distributors like Digikey and Mouser. We also offer comprehensive educational content through the Nordic Developer Academy, with two courses currently supporting the 54L Series and more on the way.Wevolver: What's the future look like for products built on the nRF54L Series?Petter Myhre: We have already engaged around 300 customers in developing with the nRF54L Series, and it is now in full volume production. This means developers and manufacturers can readily start creating and launching products based on this series.Wevolver: That's fantastic. Thank you for the insights, Petter, and we look forward to seeing the innovations that will emerge with the nRF54L Series.<a href="https://www.nordicsemi.com/Products/nRF54L15">Read more about the nRF54L Series here. </a>

At #CES2025, we caught up with Petter Myhre, Product Marketing Director, Nordic Semiconductor, who shared with us exciting new updates on the newly launched nRF54L Series.

At CES2025, Wevolver caught up with Petter Myhre, Product Marketing Director, Nordic Semiconductor, who shared with us exciting new updates on the newly launched nRF54L Series.

Nordic Semiconductor discuss the nRF54L Series at CES 2025

The Internet of Things (IoT) is reshaping our world. But behind every sleek wearable, responsive gaming controller or cutting-edge VR headset lies a monumental challenge: balancing powerful performance with minimal energy consumption. This balance is not just a technical hurdle; it's a race to unlock the next wave of connected innovation.The <a href="https://devzone.nordicsemi.com/nordic/nordic-blog/b/blog/posts/nrf54l-series-now-widely-available-for-development">nRF54L series</a>—an impactful lineup of ultra-low-power SoCs from <a href="https://www.nordicsemi.com/">Nordic Semiconductor</a>, together with software resources and utilities offers a comprehensive toolkit for IoT developers that is as versatile as it is efficient. Think longer battery lifetime, seamless wireless connectivity, and tools that let developers prototype, test, and deploy faster than ever before.&nbsp;This article looks at how the nRF54L series is empowering engineers to design for tomorrow. We'll explore its innovative developer-first approach, diving into the reasons why it's becoming the foundation of next-gen IoT development.&nbsp;<iframe width="640" height="360" src="https://www.youtube.com/embed/sgWforKsFLI?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" 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> <h2>Section 1: Why Choose the nRF54L Series?</h2>The right hardware for the IoT can make or break the success of a product. Nordic Semiconductor's nRF54L series offers a combination of ultra-low power consumption, advanced processing performance, and variety of supported wireless technologies. This series includes the nRF54L15, nRF54L10, and nRF54L05, providing a broad class of IoT applications with scalable solutions that allow developers to tailor designs to meet their needs without sacrificing performance.<h3>Flexibility of Choice for Tailored IoT Solutions</h3>The nRF54L series gives developers the choice of selecting the right SoC for their application. The nRF54L15 is the powerhouse of the series, equipped with 1.5 MB of non-volatile memory (NVM) and 256 KB of RAM. A 128 MHz Arm® Cortex-M33 processor ensures smooth performance and makes it the top choice for demanding, high-performance IoT applications, such as advanced wearables or industrial devices.&nbsp;The nRF54L10 and nRF54L05 provide smaller memory options with the same MCU capabilities, peripherals set, and multiprotocol radio for projects that prioritize cost-efficiency and compact designs. The nRF54L10 strikes a balance with 1 MB of NVM and 192 KB of RAM, while the nRF54L05, with 500 KB of NVM and 96 KB of RAM, caters to lightweight IoT applications like sensors and simpler remote devices. All SoCs in the series are available in pin-to-pin compatible package options, ensuring smooth scalability across different product lines. While the entire product line shares the same compact physical dimensions, the nRF54L15 distinguishes itself by being the only variant available in the ultra-small WLCSP package.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzM0OTYzMDE0NTk1LW5SRjU0TC1OZXh0LXdpcmVsZXNzLVNvQ3MyLmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">The nRF54L15 brings enhanced security, greater processing power, and more features but with lower power consumption for extended battery life. &nbsp;<h3>Ultra-Low Power Consumption</h3>One of the defining features of the nRF54L series is its ultra-low power consumption, achieved through Nordic Semiconductor's proprietary technologies, such as low-leakage RAM and a low-power oriented architecture.&nbsp;This power efficiency does not come at the cost of wireless performance. These SoCs feature operating voltages from 1.7V to 3.6V along with advanced sleep modes, which significantly extend battery life and increase battery lifetime, a critical advantage for devices deployed in remote or hard to access locations.The series integrates a multiprotocol 2.4 GHz radio supporting Bluetooth® 6.0, Thread, Zigbee, IEEE 802.15.4-2020, and proprietary protocols with data rates of up to 4 Mbps. The nRF54L15 achieves a sensitivity of -104 dBm at 125 kbps for long-range Bluetooth applications, ensuring reliable connectivity even in challenging environments.<h3>Packed with Advanced Features</h3>The nRF54L series is not only energy efficient but comes with features that make development easier and functionality better. A 128 MHz RISC-V coprocessor can handle additional time-critical tasks in parallel with the main processor. A comprehensive peripheral set is available to developers with a 14-bit ADC, high-speed serial interfaces, PWM units, and a Global RTC (Real Time Clock) that operates in ultra-low power sleep modes.Another standout feature is security, as the SoCs are built using Arm's TrustZone® technology offering secure execution environment. Additional hardware protection features, such as tamper detection, cryptographic accelerators, and secure key management, ensure that devices are protected against emerging threats.<h2>Empowering Developers Through Comprehensive Resources</h2>Nordic Semiconductor has created an ecosystem of tools, training programs, and community engagement to empower developers at every stage of the product lifecycle.<h3>Developer-Friendly Tools and Support</h3>Nordic Semiconductor provides QuickStart, a guided experience for developers familiar with Nordic's development tools. QuickStart allows users to quickly evaluate the board by programming precompiled software. This enables a swift "Hello World" experience by establishing a connection with the nRF Connect for Mobile application on Android or iOS.Nordic Semiconductor also provides access to the Nordic Developer Academy, which is a hub of extensive online training courses. These resources cater to varying levels of expertise, from foundational IoT development principles and foundations of supported wireless technologies, including a dedicated course for Bluetooth Low Energy, to advanced optimization techniques. The Developer Academy provides a flexible and accessible learning platform, enabling developers to learn at their own pace and deepen their understanding of the nRF54L series and the broader IoT perspective.Moreover, <a href="https://devzone.nordicsemi.com/nordic/nordic-blog/b/blog/posts/nrf54l-series-now-widely-available-for-development">Nordic's DevZone</a>, an active developer community, further enriches the development experience by providing a platform for developers to connect, share knowledge, and seek assistance from their peers and Nordic experts. Developers can gain valuable insights, troubleshoot challenges, and discover unique solutions to complex problems by interacting with Nordic’s Tech Support other members of the community. This collaborative environment creates a sense of shared learning and accelerates the development process through the collective expertise of a diverse group of engineers&nbsp;and serves as an open and accessible to all technical support.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzM0OTYxNjM4NTg2LUxlYXJuaW5nX1BhdGhzX0RldkFjYWRlbXktMTUzNng4LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">Nordic Semiconductor also provides access to the Nordic Developer Academy, which is a hub of extensive online training courses.<h3>nRF Connect SDK and Development Kit (DK)</h3>The nRF54L15 Development Kit (DK) is a versatile tool for working with the nRF54L15, nRF54L10, and nRF54L05 wireless SoCs. The nRF54L15, directly integrated into the board along with emulation support for other models, makes this single-board kit a cost-effective solution for developers to access the complete functionality of the series. The nRF Connect SDK contains a comprehensive suite of software modules, libraries, and pre-built samples, allowing developers to easily explore and optimize the capabilities of the nRF54L15. &nbsp;<h3>Interoperability and Low-Latency in Action: Focus on Exceptional User Experience in End Products</h3>Interoperability and responsiveness are very important when designing next-generation IoT devices, particularly for applications requiring instantaneous feedback and interactivity. Bluetooth Low Energy (BLE) is the primary focus of the nRF54L Series, alongside other wireless protocols for smart home and other applications. Nordic Semiconductor, renowned for its SoftDevice Bluetooth controller within the Bluetooth stack and commanding over 40% market share of all qualified BLE designs, sets the benchmark for seamless interoperability. This expertise ensures that end products built on the nRF54L Series deliver reliable and swift connections with third-party BLE-enabled devices and mobile phones.For use cases where the throughput and capabilities of standardized protocols like BLE may fall short, the nRF54L Series also provides a proprietary protocol options with up to 4 Mbps throughput. While this requires Nordic devices at both ends (limiting compatibility with mobile phones), it opens doors for high-performance applications, such as gaming controllers and virtual reality (VR) headsets. These devices demand exceptional responsiveness and low latency to deliver immersive experiences. For instance, the nRF54L15’s optimized architecture ensures ultra-fast signal processing and communication, minimizing delays. This capability is critical for gaming, where even a millisecond of lag can disrupt accuracy and immersion, and for VR, where real-time responsiveness is necessary to prevent motion sickness and maintain engagement.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzM0OTYxNzAxNTg4LTEwODBweC0yNDg3X2NsaW5lX3ZyX3N0dWRpb18yMDE5MDMxOC5qcGciLCJlZGl0cyI6eyJyZXNpemUiOnsid2lkdGgiOjk1MCwiZml0IjoiY292ZXIifX19" style="width: 100%px;" class="fr-fic fr-dib">The nRF54L Series provides the capability critical for gaming, where even a millisecond of lag can disrupt accuracy and immersion, and for VR, where real-time responsiveness is necessary to prevent motion sickness and maintain engagement.<h2>Conclusion</h2>The nRF54L series offers a unique blend of flexibility, cutting-edge technology, and comprehensive developer support and empowers engineers to&nbsp;solve the design challenges of the modern world in a simpler and more effective way. The nRF54L series provides a robust foundation for creating innovative and impactful solutions, whether for gaming, wearables, industrial IoT, or any other application that demands excellent energy efficiency and performance.Ready to innovate? Visit Nordic Semiconductor's <a href="https://www.nordicsemi.com/">website</a> to explore the nRF54L product line, access developer resources, and accelerate your IoT journey today!<h1>References</h1><ol><li>nRF54L Series now widely available for development. Nordic Semiconductor. Dev Zone. Available at: <a href="https://devzone.nordicsemi.com/nordic/nordic-blog/b/blog/posts/nrf54l-series-now-widely-available-for-development">https://devzone.nordicsemi.com/nordic/nordic-blog/b/blog/posts/nrf54l-series-now-widely-available-for-development</a> (Accessed on December 15, 2024)&nbsp;</li></ol><ol start="2" type="1"><li>Development kit for the nRF54L15, nRF54L10, and nRF54L05 wireless SoCs. Nordic Semiconductor. Available at: <a href="https://www.nordicsemi.com/Products/Development-hardware/nRF54L15-DK">https://www.nordicsemi.com/Products/Development-hardware/nRF54L15-DK</a> (Accessed on December 15, 2024)</li><li>Bluetooth Low Energy Fundamentals. Dev Academy. Available at: <a href="https://academy.nordicsemi.com/courses/bluetooth-low-energy-fundamentals/">https://academy.nordicsemi.com/courses/bluetooth-low-energy-fundamentals/</a> (Accessed on December 15, 2024)</li><li>nRF54L15 DK Hardware. Nordic Semiconductor. Available at: <a href="https://docs.nordicsemi.com/bundle/ug_nrf54l15_dk/page/UG/nRF54L15_DK/intro/intro.html">https://docs.nordicsemi.com/bundle/ug_nrf54l15_dk/page/UG/nRF54L15_DK/intro/intro.html</a> (Accessed on December 15, 2024)</li><li>Nordic Semiconductor's next generation nRF54L15 SoC to power' world's smallest' Bluetooth 6.0 compliant module. Nordic Semiconductor. Available at: <a href="https://www.nordicsemi.com/Nordic-news/2024/11/KAGA-FEI-ES4L15BA1-module-integrates-nRF54L15-SoC">https://www.nordicsemi.com/Nordic-news/2024/11/KAGA-FEI-ES4L15BA1-module-integrates-nRF54L15-SoC</a> (Accessed on December 15, 2024)</li><li>nRF54L15 System-on-Chip. Ultra-low-power wireless SoC. Available at: <a href="https://www.nordicsemi.com/Products/nRF54L15">https://www.nordicsemi.com/Products/nRF54L15</a> (Accessed on December 15, 2024)</li><li>nRF54L15 | nRF54L10 | nRF54L05 Preliminary Datasheet. Available at: <a href="https://docs.nordicsemi.com/bundle/ps_nrf54L15/page/keyfeatures_html5.html">https://docs.nordicsemi.com/bundle/ps_nrf54L15/page/keyfeatures_html5.html</a> (Accessed on December 15, 2024)</li><li>nRF54L Series: First Impressions and Comparison with the nRF52 Series. Novel Bits. Available at: <a href="https://novelbits.io/nrf54l15-unboxing-first-impressions/">https://novelbits.io/nrf54l15-unboxing-first-impressions/</a> (Accessed on December 15, 2024)</li></ol>

The nRF54L series from Nordic Semiconductor provides a versatile, ultra-low-power SoC toolkit for IoT developers, enabling enhanced battery life, seamless connectivity, and faster prototyping, positioning it as the foundation for next-generation IoT development.

Powering IoT Innovation with the nRF54L Series: Ultra-Low Power Solutions for Next-Gen Devices

<h2 dir="ltr" id="isPasted">Introduction</h2>Industrial machinery, from robots to crane booms, require sensing and guidance to ensure their effective use. Beyond the industrial world, the latest video cameras detect and compensate for movement and vibration to create high-quality imagery. In fact, accurate sensing of orientation and movement is integral to everything from communication satellites to farming equipment.Inertial measurement units (IMUs) allow the precise measurement of motion and orientation. When combined with accurate positioning information provided by global navigation satellite systems (GNSS), IMUs can provide location and velocity information, even when satellite signals are weak or obstructed.Selecting the right IMU should be easy. Manufacturer’s data sheets provide access to all the information an engineer needs to choose the perfect component for their application. And yet, engineers are designing inaccuracy into their equipment as they are unable to gain a full understanding of how IMUs perform from data sheets alone.In this paper, we will highlight three key challenges that engineers face when specifying an IMU for their next design. We will help them to read between the lines of the data sheet to understand the information they need. We will look at how manufacturers test their products, and we will explain how the environment can affect the performance of IMUs.<iframe width="540" height="370" src="https://c8056756.sibforms.com/serve/MUIFAFzOYRmakTTHP2FX2FyHP3QxXkV_prDOkSjxVq9r73O2ZYgeTBdxzjryZ1uiV-lwmna05gucMW0bsczCM_L1y82QMtCTmxYMAjh47rKxZQYNnUMylX2XNlQ7TpTNyLxACx2rLDFoQXvwdl20h6UYtI005O05w77j-WIyUR8ngfSBpL3p7bGQ8Cu-7pjUFhSkY3xZfKxVGSlQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable"></iframe> <h2 dir="ltr">Chapter 1: Getting the Whole Picture</h2>Engineers selecting the components for a new design will rely upon the manufacturer's information. The wealth of information provided by data sheets and catalogues allows the engineer to make decisions based on the component’s predicted performance. The key attributes that must be understood when selecting IMUs are bias instability and angle random walk (ARW). Bias instability is caused by tiny fluctuations in an IMU’s zero-bias level. This is the reading that the sensor delivers when it is at rest, and therefore provides the baseline for an IMU that is stationary. IMUs are affected by a range of external conditions, including variations in temperature and vibration, which reduce the accuracy and stability of the IMU's output. This change is characterized by a slow, long-term drift and is measured in degrees of drift per second (deg/s).In contrast to bias instability, angle random walk is caused by random high-frequency noise inside the IMU which causes variations in the measurement of angular velocity over time. The errors that ARW tries to quantify grow with the square root of time, and so the accumulated angle error will grow over a long period.Both attributes are, therefore, heavily influenced by time, a problem that is made worse by the dynamic conditions that IMUs are intended to measure. However, the data that is typically provided in IMU data sheets does not reflect this dynamic nature, and both bias instability and ARW are often published as a single number. This reduction of a complex system to a single number does not provide the engineer with a clear prediction of its performance over time. By relying on single attributes, engineers run the risk of designing inaccuracies into their device before it is even used.Instead of relying on the single value of the gyro bias instability and ARW, engineers can turn to Allan deviation plots. An Allan deviation plot (or Allan variance plot) is a graphical tool that provides a more useful understanding of the stability and noise characteristics of IMUs. The plot is unique to each IMU and helps identify the effects of different types of noise by showing how the variance of a sensor’s output changes over different averaging times. This is especially useful for assessing the drift and noise behaviour over time.This time dependency is the key advantage of using Allan deviation instead of traditional standard deviation. Standard deviation is a useful tool if the mean of the data is expected to be constant, and the measurements do not drift over time. This is not the case with IMUs. An Allan plot is derived from data collected from the IMU over a period of time, calculated at an interval known as tau (𝜏). This represents the averaging time, and the higher the tau, the more that individual extreme readings will be averaged out.The image below shows a typical Allan deviation plot for an IMU, in which the low point corresponds to the bias instability, whereas the value corresponding to tau of 1 sec (1 second averaging) represents the angular random walk, reflecting the higher frequency fluctuations that define ARW.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1733673242419-banner+epson.jpg" style="width: 100%px;" class="fr-fic fr-dib">Another data point concerns warm-up time. Extreme temperatures can affect the warm-up time of the IMU. This is the period after activation that the IMU needs to reach its operational state. In just one example, after hours exposed to sub-zero temperatures, the warm-up time for an IMU may be considerably longer than published to allow the internal components to stabilize before they can provide accurate readings.To avoid designing undesired inaccuracy into a new device, it is therefore vital for the engineers to access the best possible data. The preferred path for the engineer is to work with an IMU manufacturer that can provide this comprehensive information, for the alternative is for the engineer to conduct their own evaluation, a time-consuming process.While the information presented in data sheets is important, the engineer will only gain a real insight into the performance of their chosen component by understanding the underlying data and how it will affect their application in the long run.<h2 dir="ltr">Chapter 2: IMUs in the Real World</h2>Accurate and comprehensive information is therefore vital, but it is important for the engineer to understand the conditions under which it was obtained. Systems and equipment that use IMUs are regularly deployed beyond the safe environment of the laboratory into the real world. The conditions they encounter can have a significant effect on the performance of IMUs.An example of these tough conditions can be found in modern farming. The agricultural industry is embracing the latest sensing technology, collecting data to maximize efficiency. &nbsp;This data is used to make decisions, from identifying optimum soil conditions to deploying the right resources.&nbsp;Accurate positioning is essential for the smart farm. The ability to precisely control planting, fertilizing and harvesting activities allows the farmer to improve efficiency, yields, and sustainability. The huge growth in the development of autonomous tractors, harvesters, and drones places even more emphasis on navigation and positioning. These systems make use of global navigation satellite systems (GNSS) to allow these machines to operate within centimeters of their intended paths, without the need for human intervention.However, GNSS signals may not always be available as satellite signals can become disrupted or blocked. Atmospheric conditions, interference from structures and geographical features, along with the orbital geometry of the satellites themselves can all cause loss of signals. Without satellite guidance, autonomous machinery cannot obtain the accurate position that is so important to precision farming.Under these circumstances, the IMU becomes the principal means by which the equipment can locate their position. Using a process of dead reckoning, the IMU can measure the movement from the last known position provided by GNSS until the signal can be reacquired. The same method can be employed by a huge range of industries far from the smart farm, from the delivery of medical supplies by drone into remote locations to the automated loading of ships at ports.This reliance on IMUs in the real world means that they must withstand a range of conditions. Some of the most important effects to consider are those caused by shock and vibration. IMUs can be affected by both high and low frequencies. Some frequencies can cause an effect called sensor saturation in which the IMU can no longer work correctly as the vibration exceeds the IMU’s limiting value. Engineers must also be aware of the physical damage that vibration and sudden shock can cause to equipment.Engineers must also understand the effect of extreme temperatures on IMUs. In the earlier example, we looked at the need for accurate positioning on the smart farm. The agricultural environment is one of the harshest in the world, and vehicles are designed to function in an extraordinary range of conditions. Whether deployed to the frozen tundra in the Arctic circle or the unforgiving heat of deserts, equipment is exposed to ambient temperatures from -40°C to near the boiling point of water.This range of temperatures has a significant impact on the accuracy and performance of IMUs. Bias instability changes with temperature, which can lead to cumulative errors, especially for measurements based on integration over time. To complicate matters further, the drift in bias caused by changes in temperature are often nonlinear. This means that the designer needs to calibrate their system over the expected operating temperature range to ensure accuracy.Engineers must therefore understand the environment into which their equipment will be deployed. Identifying harsh conditions on the road or in the factory will allow engineer to choose the correct IMU based on accurate data. This may require information obtained from the IMU manufacture that is not contained in the data sheet. It is essential to understand how temperature will affect warm-up time, and to request a calibration profile that details temperature-dependent drifts.<h2 dir="ltr">Chapter 3: Consistency is the Key</h2>While it is important for the engineer to understand the conditions to which their design will be exposed, it is also crucial to know how the data provided by the manufacturer was created. This has important implications for consistency. Data sheets for IMUs often present typical performance values, without providing clear information about how this information was obtained. In many cases, the published information is an average, but the data sheet will rarely provide details about the statistical methodology used to obtain the average. Without the all-important description of this typical performance, the engineer can only guess how the IMU will perform in their specific application.When evaluating IMUs, it is important to understand the level of statistical confidence behind the performance data. Where some manufacturers will publish performance at a 1-sigma level, others will use 2-sigma. The statistical difference between different sigma levels has important implications for high-performance applications in which consistency is key.Sigma levels are use used in statistics to describe a confidence level in the data provided. In a normal distribution of data, a 1-sigma (1σ) level represents one standard deviation away from the mean. At this level, roughly two-thirds (in fact, 68.27%) of the data values will fall within this one standard deviation from the mean. In real terms, it means that there is a two-thirds probability that any single measurement will fall within this range.However, if a manufacturer bases their data on a 2-sigma (2σ) level, this probability rises to more than 95%. As a result, any one measurement will fall within the predicted range 19 times out of 20, delivering a far higher level of confidence in the data provided. In the context of IMUs, this confidence translates into an expectation of accuracy over time.This variation in predicted consistency is further complicated by the testing regime employed by the manufacturer. Some manufacturers adopt a strategy of batch testing, evaluating only a small number of units to provide the data required. Other manufacturers may conduct multiple tests on a single unit in the expectation that this will provide an accurate prediction of the performance of the entire range. The result is that the listed performance may not accurately reflect the variability between different IMUs from the same production batch. This variability can be significant, particularly for critical characteristics like bias instability.Unfortunately, the only way to truly understand how an IMU will perform in a real-world application is for the engineer to perform their own evaluation. While data sheets can provide a baseline, real-world testing is necessary to understand the variability between units and ensure consistent performance in the field. Working with a trusted manufacturer that publishes clear and comprehensive information can go a long way to helping the engineer with their understanding.<iframe width="540" height="370" src="https://c8056756.sibforms.com/serve/MUIFAFzOYRmakTTHP2FX2FyHP3QxXkV_prDOkSjxVq9r73O2ZYgeTBdxzjryZ1uiV-lwmna05gucMW0bsczCM_L1y82QMtCTmxYMAjh47rKxZQYNnUMylX2XNlQ7TpTNyLxACx2rLDFoQXvwdl20h6UYtI005O05w77j-WIyUR8ngfSBpL3p7bGQ8Cu-7pjUFhSkY3xZfKxVGSlQ" frameborder="0" scrolling="auto" allowfullscreen="" style="display: block;margin-left: auto;margin-right: auto;max-width: 100%;" class="fr-draggable"></iframe> <h2 dir="ltr">Conclusion</h2>Selecting the right inertial measurement unit is a complex task. Not only are IMUs required to accurately measure movement, but they are expected to deliver high reliability in some of the most demanding conditions..Engineers need to understand how these conditions will affect the performance of their IMU. The roles played by extremes of temperature and the physical demands of dynamic applications must be considered before the engineer can have confidence on their design. Unfortunately, some manufacturers do not provide easy access to the detailed information that engineers need. Therefore, when selecting an IMU, here are the key considerations for engineers:<ul><li dir="ltr">Remember that the data sheet might not contain the depth of information required. Do not rely on single-number attributes, and obtain Allan deviation plots to gain a full understanding of the device’s performance.</li><li dir="ltr">Device testing takes place in the controlled environment of the laboratory, but the real-world is not so accommodating. Extremes of temperature and physical demands play a huge role in the reliability and accuracy of IMUs. Engineers should ensure that they understand their environment.</li><li dir="ltr">Take the time to understand how IMUs are tested. Confidence in performance comes from extensive testing methods, and clearly published data from the manufacturer. If necessary, engineers should be ready to conduct their own evaluation.</li></ul><a href="https://global.epson.com/products_and_drivers/sensing_system/imu/">Epson</a> manufactures a comprehensive range of IMUs for a huge array of applications, from earthquake detection to the precise positioning of satellites in space. Epson creates highly capable sensing systems that offer outstanding precision, high stability, and low noise to deliver confidence to design engineers in the most demanding industries.

Understanding IMU data sheets, manufacturers' testing methods, and the impact of environmental factors on performance.

Three Key Considerations for Selecting IMUs

Microcontrollers have become ubiquitous in modern life, we find them in a multitude of places and applications including.&nbsp;<ul type="disc"><li>Consumer Electronics: Home appliances, battery management systems, and chargers.</li><li>Automotive Industry: Engine control units, anti-lock braking systems, airbags, and collision protection systems.</li><li>Industrial Automation: Motor controllers and process control systems.</li><li>Medical Devices: Infusion pumps and wearable health monitoring devices.</li><li>Internet of Things (IoT): Smart home devices and environmental monitoring systems.</li></ul>While a range of applications deploy microcontrollers and present different challenges, consumer and IoT sectors require low-cost and good supporting development environments with several libraries to ease integration and development. In contrast automotive, medical, and industrial automation applications often require the microcontroller to operate in power-constrained and harsh environments where failure could result in loss of life or environmental damage. Therefore, robust design and reliable operation in these applications are paramount - this something we will come back to discuss in detail in a later article.&nbsp;Overview of microcontroller architecturesBefore diving into development methodologies and techniques, it's essential to understand common architectural features of microcontrollers. While traditionally 8- and 16-bit microcontrollers have been very popular (for example I learned about microcontrollers with 8-bit PICS at university), we have seen a shift to more capable 32-bit processors.&nbsp;At the heart of a microcontroller is the processor core, typically 32-bitin modern designs. This could be an ARM Cortex-M series processor or a RISC-V RV32 core. The application program executed by the microcontroller is stored in non-volatile memory (such as Flash memory), and the microcontroller also includes volatile memory (SRAM) for application execution, data storage and manipulation.To help reduce system integration challenges and bill-of-materials costs, most microcontrollers integrate both non-volatile and volatile memories internally, reducing the need for external components and simplifying the overall system design.Some microcontrollers feature multiple processor cores, which can enhance processing capabilities. However, without an operating system, such as Linux to manage and allocate tasks across cores, developers are presented with several challenges to effectively leverage the dual cores. Notably, even affordable microcontrollers like the Raspberry Pi Pico (RP2040) offer dual-core processing.Having multiple cores can increase the performance of the system, however, there are considerations and drawback of these multiprocessor systems when we are working with bare metal or RTOS, including:&nbsp;<ul><li>Resource Constraints: Microcontrollers have limited memory and processing power. Parallel programming in such environments requires management of these system resources to prevent bottlenecks or conflicts.&nbsp;</li><li>Inter-Core Communication: Coordinating tasks between cores necessitates reliable communication mechanisms. Implementing these can be non-trivial due to the hardware limitations and the need for low-latency interactions.</li><li>Synchronization Issues: Without proper synchronization, parallel tasks can lead to race conditions, deadlocks, or data corruption. Ensuring thread-safe operations requires additional complexity in code design.</li><li>Debugging Challenges: Debugging concurrent code on microcontrollers is more difficult due to limited tooling and visibility into the system's state during execution.</li></ul>Peripherals and interfacesTo interact with the external world, microcontrollers include a variety of peripherals connected to the processor core. Commonly provided peripherals include:<ul type="disc"><li>Standard Communication Interfaces: UART, SPI, I²C, and Ethernet.</li><li>GPIO: General-Purpose Input/Output pins for interfacing with sensors, actuators, and other devices.</li><li>Timers and Watchdogs: For timing operations and system reliability.</li><li>Real-Time Clocks (RTC): For timekeeping functions.</li><li>Specialized Interfaces: Depending on the application, microcontrollers may include interfaces like CAN or CAN FD for automotive applications, or 1553B and SpaceWire for aerospace and space applications.</li></ul>Many microcontrollers also provide mixed-signal capabilities, such as analogue-to-digital Converters (ADCs). These typically have sampling frequencies between 100 kHz and 1 MHz, suitable for control applications like measuring voltages, currents, and temperatures. For example, they can easily sample sensors like Platinum Resistance Thermometers (PRTs) and Negative Temperature Coefficient (NTC) thermistors. Again, this helps reduce the system bill of material cost and enables a smaller overall solution, critical for many constrained applications.Depending on the peripherals required for the applications and the available internal memory resources, we may need to consider using external memories if libraries are used to support more complex peripherals such as the lightweight IP stack supporting the Ethernet communications.Sadly, our applications do not always work first time, so an essential aspect of working with microcontrollers is the ability to program and debug them using standard interfaces like JTAG or Serial Wire Debug (SWD). These interfaces allow developers to download software to the microcontroller and perform in-depth debugging of their applications, performing tasks such as break pointing, inspecting variable values, and observing registers within the processor to ensure they are configured correctly.&nbsp;One of the most challenging aspects of working with a microcontroller in your application is choosing the most appropriate one. There are several aspects which can be considered to help identify the correct processor:&nbsp;<ul type="disc"><li>Performance: Processing speed and capabilities needed for the application.</li><li>Memory Resources: Adequate onboard Flash and SRAM for the application code and data.</li><li>Peripheral Availability: Necessary interfaces and peripherals for the application.</li><li>Environmental Conditions: Operating temperature ranges, such as industrial or automotive standards.</li><li>Power Consumption: Especially important in battery-powered or energy-harvesting applications.</li><li>Development Ecosystem: Availability of development tools, libraries, and community support.</li></ul>Another aspect which helps us understand the processor’s processing capabilities and supports our identification of a suitable processor is the performance benchmarking. Benchmarks enable us to compare the processing power of several different microcontrollers despite having differing clock speeds or number of cores. One common benchmark is Dhrystone MIPS (Millions of Instructions Per Second). While it has limitations, Dhrystone is widely used, and many processors provide a DMIPS/MHz rating, indicating the performance per MHz of clock frequency. This allows developers to estimate performance at different operating frequencies.&nbsp;There is a range of microcontrollers available from many different vendors; over this series we will look at several of these. However, one of the most popular microcontroller entry-level platforms of recent years is Arduino. Arduino provides developers with a range of development boards based on simple microcontrollers, supported by an extensive development ecosystem that includes an integrated development environment (IDE), libraries, and programming tools. The vibrant Arduino community offers a wealth of resources, from project tutorials to blogs and forums. Since its introduction, Arduino has played a significant role in popularizing embedded microcontrollers and low-level programming, especially among young people considering careers in engineering and software development.Next StepsThis introduction provides a foundational understanding of microcontrollers and their role in embedded systems. In subsequent articles, we will explore various development methodologies, techniques, and best practices for designing and implementing microcontroller-based applications.

This article begins with a general introduction to microcontrollers, what they are and how we might use them and their challenges. 

An introduction to microcontrollers

In the fast-paced world of electronics and innovation, having access to the right tools is essential for designers and engineers looking to bring their concepts to life quickly and efficiently. Development kits are a key resource in this process, offering pre-built solutions that allow for faster prototyping and testing of new ideas. Mouser Electronics, a leading global distributor, is renowned for providing one of the most extensive ranges of off-the-shelf development kits, ensuring that designers can access the tools they need when they need them.In this article, Mouser’s Director of Technical Content for EMEA, Mark Patrick, shares his expert insights by presenting his ‘Top 5 Picks’ from the latest development kits available. These kits have been carefully selected based on their innovative features, ease of use, and the potential they offer to accelerate the design process. Whether you're working on AI applications, IoT solutions, or embedded systems, these development kits can give your project the jumpstart it needs.<h2>Long-range connectivity</h2>Digi XBee® XR 868&nbsp;This development kit includes the Digi XBee 868 RF MHz module with a U.FL antenna connector, antennas, and a development board. It supports long-range connectivity applications in Europe, operating between 863MHz and 870MHz. The module facilitates point-to-point and mesh networking with a line-of-sight range exceeding 14 kilometers, ideal for the agriculture and energy sectors. The device employs intelligent interference management using Listen Before Talk and Adaptive Frequency Agility, reducing interference by scanning frequencies and shifting channels seamlessly.<a href="https://www.mouser.com/new/embedded-solutions/engineering-tools/digi-xbee-xr-868-kit/n-8mwysZ1npagf">XBee® XR 868 Development Kit - Digi | Mouser</a><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1729582453944-digi.jpg" style="width: 100%px;" class="fr-fic fr-dib"><h2>Curiouser and curiouser</h2>Microchip WBZ450 EV22L65AMicrochip’s WBZ450 Curiosity board is an efficient, modular development platform that supports rapid prototyping and demonstrates the features, capabilities, and interfaces of Microchip’s WBZ450PE BLUETOOTH® Low Energy and Zigbee® RF module. The EV22L65A board offers integrated programming/debugging features using the PICkit™ Onboard 4 (PKOB4) debugger interface. A Micro-USB cable is required to power up and program the board.<a href="https://www.mouser.com/new/embedded-solutions/engineering-tools/microchip-ev22l65a-board/n-8mwysZ2puw22">WBZ450 Curiosity Board (EV22L65A) - Microchip Technology | Mouser</a><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1729582723571-micro.jpg" style="width: 100%px;" class="fr-fic fr-dib"><h2>Arm-based MCU&nbsp;</h2>STMicro STM32H7S78-DK Discovery kitSTMicroelectronics’ STM32H7S78-DK Discovery kit demonstrates and develops applications for the Arm® Cortex®-M7 core-based STM32H7S7L8H6H microcontroller. The kit comes with various hardware features, including USB Type-C™, Octo-SPI flash memory, Hexadeca-SPI PSRAM devices, audio codec, digital microphones, ADC, user button, and flexible extension connectors. These connectors facilitate easy wireless connectivity, analog applications, and sensor expansion.<a href="https://www.mouser.com/new/embedded-solutions/engineering-tools/stm-stm32h7s78-dk-kit/n-8mwysZ2cjsva">STM32H7S78-DK Discovery Kit - STMicro | Mouser</a><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1729582777405-st.jpg" style="width: 100%px;" class="fr-fic fr-dib"><h2>Rugged and reliable embedded wireless</h2>Advantech WLNNA&nbsp;Advantech’s WLNNA Series evaluation kit is a platform for evaluating, testing and developing Airborne Enterprise Device Server Modules. The Advantech WLNNA kit offers size, cost, power consumption, and performance advantages over other wireless solutions. Ideal for rugged and reliable applications needing an embedded IEEE 802.11a/b/g/n compliant wireless engine, the kit includes a WLNNA Series Evaluation Board with connectors and headers providing access to all module interfaces.<a href="https://www.mouser.com/new/embedded-solutions/engineering-tools/advantech-wlnna-kit/n-8mwysZ27k4mu">WLNNA Series Evaluation Kit - Advantech | Mouser</a><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1729582820389-brief+2.png" style="width: 100%px;" class="fr-fic fr-dib"><h2>IoT control</h2>M5Stack M5NanoC6 boardThis board features an ESP32-C6FH4 MCU supporting Wi-Fi 6, Zigbee®, and an infrared emitter for controlling infrared IoT devices. The device's ceramic antenna ensures stable wireless communication. Programmable RGB beads enable personalized visual effects. The Grove interface allows flexible expansion of various M5 devices, which are customizable for different communication protocols.<a href="https://www.mouser.com/new/embedded-solutions/engineering-tools/m5stack-m5nanoc6-board/n-8mwysZ2sl8dv" id="isPasted">M5NanoC6 Board - M5Stack | Mouser</a><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1729582849615-m5.jpg" style="width: 100%px;" class="fr-fic fr-dib">

In this article,  Mouser’s Director, Technical Content, EMEA, Mark Patrick, presents his ‘Top 5 Pick’ of recently-released dev kits.

The development tools you need

The latest large language models (LLMs), like the newly released ChatGPT-4o, are truly astonishing. They are multimodal, meaning they have multiple senses and can interpret text, images, and audio information and respond in a seemingly human-like manner.But how do they relate to edge AI, and what role does Edge Impulse play in this? This question comes up frequently in a range of conversations.Today we are sharing an exciting new Edge Impulse functionality that shows just one of the powerful ways that LLMs can be utilized on the edge: using GPT-4o to train a 2,000,000x smaller model, that runs directly on device.<iframe width="640" height="360" src="https://www.youtube.com/embed/Jou0aRgGiis?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" 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;</iframe><h3 id="isPasted">The challenge of LLMs for real-time insights</h3>Let's say a business has a camera pointed at their factory floor. A manager can ask an LLM, "Is there a person not wearing a hard hat standing close to the machine?" The LLM is capable of analyzing the frame and answering yes or no; that response can then be used to trigger actions according to predetermined safety protocols.This is incredibly powerful because 1. the model understands what it sees, and 2. you can use natural language to ask questions about what is happening. This approach is called zero-shot learning, where you don't need to train a model beforehand.However, there are downsides to deploying zero-shot models in real environments. State-of-the-art LLM models have hundreds of billions of parameters, making them huge and slow. They typically run in the cloud, leading to latency issues. Even fast models like ChatGPT-4o take more than a second to analyze a single image, which is too slow for many real-time applications.<a href="https://form.jotform.com/242533284499365"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1728891006740-5+Rising+Trends+for+AI+Adoption+in+Manufacturing+%283%29.png" style="width: 100%px;" class="fr-fic fr-dib"></a><h3>One solution: Labeling data with LLMs and Edge Impulse</h3>To address these issues, we need similar capabilities that can run closer to or even on the edge. Imagine the same factory floor but instead with a simple camera where everything runs locally. This setup offers low latency and low cost, without the need for cloud services.Using this type of system locally with LLMs isn't feasible, given the massive size of LLM models. However, with Edge Impulse, one can use an LLM's understanding to train a much smaller model. This process involves a form of transferring knowledge from a large model to a smaller one.Edge Impulse specializes in bringing AI to the edge, with over 300,000 projects created to build AI applications that run self-contained on devices from Arm Cortex-M (via <a href="https://www.edgeimpulse.com/blog/announcing-arm-keil-integration/">open-CMSIS</a>, reaching over 10,000+ devices) to <a href="https://edgeimpulse.com/nvidia/nvidia-tao">Nvidia</a>-based GPUs and beyond.The new Edge Impulse LLM functionality allows a user to bring LLM-based AI to the edge to automatically analyze and label visual data, including video uploads, and apply a specific understanding of what's in frame without needing someone to manually input any labels. Using the LLM's intelligence on just a specific request allows Edge Impulse to train a vision-based model from it that is compact enough to run on-device. It's a powerful and exciting application.<table><tbody><tr><td><h3>New whitepaper: Discover the 5 AI Trends Transforming Manufacturing</h3><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1728891039779-1728891039779.png" class="fr-fic fr-dii">The whitepaper, "5 Rising Trends for AI Adoption in Manufacturing," offers key insights into how artificial intelligence is transforming manufacturing processes. It explores survey data from over 150 industry leaders, revealing that optimizing production and improving product quality are top goals driving AI adoption. The report also discusses the rise of AI solutions for worker safety, real-time insights to boost profitability, and the growing importance of internal expertise in implementing AI. Download the full whitepaper to gain a deeper understanding of these trends and how AI/ML is shaping the future of manufacturing.<a href="https://form.jotform.com/242533284499365" target="_blank" rel="nofollow" class="button-main-action">DOWNLOAD YOUR FREE COPY</a></td></tr></tbody></table><h3>Project walkthrough</h3>Let's build a project to see how this works. In the above video I walked through my house, capturing a video of my living room filled with my kids' toys. Using ChatGPT, I can ask questions about this video, such as whether a children's toy is in view. Here's how we can create a smaller model to perform this same task, on-device:<ol><li>Data Collection: I recorded a video of my living room.</li><li>Data Processing: I uploaded the video to Edge Impulse. The data was initially unlabeled.</li><li>Labeling with GPT-4o: Using the new transformation block "Label image data using GPT-4o," I asked GPT-4o to label the images. The block discards any blurry or uncertain images, providing a clean dataset.</li><li>Model Training: I split the video into images, resulting in about 500 labeled items. I used <a href="https://edgeimpulse.com/nvidia/nvidia-tao" rel="noreferrer">NVIDIA TAO</a> to train a small model with these images. The model had only 800,000 parameters, significantly smaller than the original LLM.</li><li>Deployment: I deployed the model, running at 10 frames per second on an Arduino Nicla Vision. The model accurately detected toys on-device, in real-time, without requiring cloud services.</li></ol><h3>Results</h3>The small model performed exceptionally well, identifying toys in various scenes quickly and accurately. By distilling knowledge from the large LLM, we created a specialized, efficient model suitable for edge deployment. The smaller model ran at 50 frames per second in a browser on my iPhone and even on a microcontroller with minimal accuracy loss.<hr><h3 id="isPasted">Download the whitepaper: 5 AI Trends Transforming Manufacturing</h3><div data-message-author-role="assistant" data-message-id="a9ce89dd-4eb9-44c7-9d28-e3c7d10f7094" dir="auto" data-message-model-slug="gpt-4o"><div data-message-author-role="assistant" data-message-id="1c2c7603-add5-4aa4-84c9-81aa2c1371a2" dir="auto" data-message-model-slug="gpt-4o">Stay ahead of the curve on how AI is transforming businesses with the whitepaper "5 Rising Trends for AI Adoption in Manufacturing." The guide offers valuable insights to help leaders implement AI strategies that optimize production, improve product quality, and drive innovation. Download your free copy now:<iframe id="JotFormIFrame-242533284499365" title="Edge Impulse Form" allowtransparency="true" src="https://form.jotform.com/242533284499365" frameborder="0" style="min-width:100%;max-width:100%;height:900px;border:none;" scrolling="no" 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></div></div>

The latest large language models (LLMs), like the newly released ChatGPT-4o, are truly astonishing. They are multimodal, meaning they have multiple senses and can interpret text, images, and audio information and respond in a seemingly human-like manner.

Bringing Large Language Models to the Edge with GPT-4o and NVIDIA TAO

Arduino micro-controller on the left, Raspberry Pi in the middle and C.H.I.P. single-board computer on the right

This article provides a comprehensive analysis of Arduino vs Raspberry Pi, highlighting their essentials, key features, and recent developments, helping you make an informed decision for your next project. 

Arduino vs Raspberry Pi: Choosing the Right Platform for Your Next Project

This article will guide you through the key features, functions, and configurations of the ESP8266 Pinout, setting the foundation for successful IoT implementations.

ESP8266 Pinout: Unlocking the Power of IoT's Favorite Microcontroller

I3C is becoming a strong alternative to I2C. Learn about the main differences, benefits, and uses of these two important communication protocols. Explore the world of inter-integrated circuit communication and see which protocol is best for your next project.

I3C vs I2C: Unraveling the Battle of Communication Protocols

Espressif ESP32 series microcontroller module

This guide serves as a roadmap for engineers to navigate the intricacies of the ESP32 pinout, understand its significance, and explore its applications in modern engineering projects. 

ESP32 Pinout: A Comprehensive Guide for Engineers

This article was written by Adam Taylor for Mouser Electronics<h2 id="isPasted">Introduction</h2>In this project, we will configure the AMD Kria™ KR260 Robotics Starter Kit to control a Trossen Robotics ReactorX 150 robot arm. This complex robot arm uses <a href="https://www.mouser.com/new/robotis/robotis-dynamixel-x-modules/" rel="nofollow" target="_blank" data-internal="false">ROBOTIS DYNAMIXEL</a> servos, which contain not only motors but also microcontrollers and networking capability. While this enables the complex motor drives needed for robotics applications, it also means that each servo has several different drive and control mechanisms. Typically, when working with servos and robotics applications of this complexity, significant processing is required to plan and address the robotic movement.To interact with and control such robots, engineers often use the <a href="https://www.ros.org/" rel="nofollow" target="_blank" data-internal="false">Robot Operating System (ROS)</a>, which runs on Linux. The most used version of ROS is ROS 2, which updated the ROS frameworks and tools to work with a wider variety of environments, provide support for real-time environments, and use significantly updated APIs. ROS 2 provides developers with functionalities such as hardware drivers, robot models, datatypes, and support for perception and simultaneous localization and mapping (SLAM). ROS 2 also provides a series of tools that aid in the development or operation of systems such as RViz, which provides a 3D visualization, and Gazebo, a simulator.ROS 2 is built around a graph architecture; within this architecture, processing takes place in nodes that can receive and post data about the node, such as sensor, control, planning, actuator positioning, or current state. Nodes are connected on the ROS graph by topics, which are communication pipelines to which nodes can publish data and receive information. Along with nodes and topics, a node may also advertise services. The services have a single result, such as capturing a frame of video, sampling a sensor, or opening an actuator.<h2>Bill of Materials</h2><ul><li><a href="https://www.mouser.com/new/xilinx/xilinx-kria-kr260-kit/" rel="nofollow" target="_blank" data-internal="false">AMD Kria™ KR260 Robotics Starter Kit</a></li><li>Monitor with DisplayPort™ compatibility</li><li>USB keyboard and mouse</li><li><a href="https://www.trossenrobotics.com/reactorx-150-robot-arm.aspx" rel="nofollow" target="_blank" data-internal="false">ROBOTIS ReactorX In150</a> robotic arm</li></ul><h2>Resources</h2><ul><li><a href="https://ubuntu.com/certified/202202-29985" rel="nofollow" target="_blank" data-internal="false">Ubuntu Linux distribution image for the AMD Kria™ KR260 Robotics Starter Kit</a> (Ubuntu)</li><li><a href="https://www.xilinx.com/products/som/kria/kr260-robotics-starter-kit/kr260-getting-started/setting-up-the-sd-card-image.html" rel="nofollow" target="_blank" data-internal="false">Getting Started with the AMD Kria KR260 Robotics Starter Kit</a> (AMD)</li><li><a href="https://sourceforge.net/projects/vcxsrv/files/vcxsrv/1.20.14.0/" rel="nofollow" target="_blank" data-internal="false">VcXsrv Windows X Server Files</a></li></ul><h2>Software Setup</h2>In this project, we will install the Trossen Robotics packages and ROS 2 on the AMD Kria™ KR260 Robotics Starter Kit, which will enable you to control the robot arm.<h3>Installing Ubuntu</h3>Start by downloading and installing the Ubuntu Linux distribution image for the AMD Kria™ KR260 kit, available in the Resources section. Once the image is available, flash the image to an SD card following the instructions provided by AMD in Getting Started with Kria KR260 Robotics Starter Kit in the Resources section.Once you have successfully booted the AMD Kria KR260 kit, you will need to update the Ubuntu installation to ensure we can install ROS 2 correctly.<ol><li>Install resolvconf.</li></ol><code>&nbsp; &nbsp;sudo apt update</code><code>&nbsp; &nbsp;sudo apt install resolvconf</code><ol start="2"><li>With resolvconf installed, ensure it is running.</li></ol><code>&nbsp; &nbsp;sudo systemctl status resolvconf.service</code><ol start="3"><li>Once you have confirmed the service is running, add your preferred DNS server. In this example, we use Googles DNS.</li></ol><code>&nbsp; &nbsp;echo "nameserver 8.8.8.8" | sudo tee -a /etc/resolvconf/resolv.conf.d/head</code><code>&nbsp; &nbsp;echo "nameserver 8.8.4.4" | sudo tee -a /etc/resolvconf/resolv.conf.d/head</code><ol start="4"><li>Because we made changes, we need to restart the services.</li></ol><code>&nbsp; &nbsp;sudo systemctl restart resolvconf.service</code><code>&nbsp; &nbsp;sudo systemctl restart systemd-resolved.service</code><ol start="5"><li>Prevent Ubuntu on the KR260 from going to sleep.</li></ol><code>&nbsp; &nbsp;sudo gsettings set org.gnome.desktop.session idle-delay 0</code><code>&nbsp; &nbsp;sudo systemctl mask suspend.target</code><h3>Installing ROS 2</h3>To install ROS 2 and the packages to control the Trossen Robotics X Series arm, we will modify the instructions slightly to those used for the Raspberry Pi, which, like the AMD Kria™ KR260 kit, uses the Arm64 (aarch64) instruction set architecture.The latest version of ROS 2 supported by Trossen’s libraries is ROS 2 Humble. Use the following commands to install ROS 2 and the Trossen libraries:<code>cd ~</code><code>sudo apt install curl</code><code>curl 'https://raw.githubusercontent.com/Interbotix/interbotix_ros_manipulators/main/interbotix_ros_xsarms/install/rpi4/xsarm_rpi4_install.sh' &gt; xsarm_rpi4_install.sh</code><code>sed -i 's/sudo apt-get update &amp;&amp; sudo apt -y upgrade/sudo apt-get update/g' xsarm_rpi4_install.sh</code><code>chmod +x xsarm_rpi4_install.sh</code><code>./xsarm_rpi4_install.sh -d humble -j rx150</code><h2>Demo Application</h2>With ROS 2 installed on the AMD Kria™ KR260 kit, we will run one of the provided demo applications. Open two terminal windows on the KR260.<ol><li>In the first terminal window, enter the following command:</li></ol><code>&nbsp; &nbsp;ros2 launch interbotix_xsarm_control xsarm_control.launch.py robot_model:=rx150</code><ol start="2"><li>In the second terminal, enter the following command:</li></ol><code>&nbsp; &nbsp;python3 /home/ubuntu/interbotix_ws/src/interbotix_ros_manipulators/interbotix_ros_xsarms/interbotix_xsarm_control/demos/python_ros2_api/bartender.py</code>This will run an application that demonstrates the control of the robot arm.<h3>Demo Breakdown</h3>By examining the code in this application, we can see how we can control the arm using the Python programming language. First, we need to import the InterbotixManipulatorXS arm package from the InterbotiX libraries we installed. To do this, enter the following command: <code>from interbotix_xs_modules.arm import InterbotixManipulatorXS</code>With these packages installed, we can start creating applications that manipulate the arm using a Python application.Looking at the example code, we can see the first thing we do is initialize it with the parameters of the robot, the model, type, and its end effector.With the robot (shown as <code>bot</code> in the code) defined, the application first checks the robot has the correct number of joints for the demo. Once it has been confirmed as being suitable for the demo, the robot is controlled by using several Python commands that set the pose, or single positions, as required. The gripper can also be opened and closed using Python calls.<code>bot = InterbotixManipulatorXS("rx150", "arm", "gripper")</code><code>&nbsp; &nbsp; if (bot.arm.group_info.num_joints &lt; 5):</code><code>&nbsp; &nbsp; &nbsp; &nbsp; print('This demo requires the robot to have at least 5 joints!')</code><code>&nbsp; &nbsp; &nbsp; &nbsp; sys.exit()</code><code>&nbsp; &nbsp; bot.arm.set_ee_pose_components(x=0.3, z=0.2)</code><code>&nbsp; &nbsp; bot.arm.set_single_joint_position("waist", np.pi/2.0)</code><code>&nbsp; &nbsp; bot.gripper.open()</code><code>&nbsp; &nbsp; bot.arm.set_ee_cartesian_trajectory(x=0.1, z=-0.16)</code><code>&nbsp; &nbsp; bot.gripper.close()</code>Finally, the demo ends by safely positioning the robot to its home position.<code>&nbsp; &nbsp; bot.arm.go_to_home_pose()</code><code>&nbsp; &nbsp; bot.arm.go_to_sleep_pose()</code>Knowing this, we can start creating own custom applications, as shown in <a href="https://youtu.be/g4xX4aowwI8" rel="nofollow" target="_blank" data-internal="false">this video</a>. But first, we need to be able to remotely develop applications on the AMD Kria™ KR260 board.<h2>Remote Development</h2>To develop our remote application, we will use Visual Studio Code on the development machine. The Python application we create using Visual Studio Code on our development machine will be in the file system of the AMD Kria™ KR260 kit. This also has the benefit of requiring no connected display, keyboard, or mouse, as we can access everything from the development environment.We also want to be able to remotely view the visualization of the robot arm as we develop our application (in simulation mode or actual execution).To enable remote development and visualization, we must establish SSH connection and enable X11 forwarding.<ol><li>Use Windows Powershell to install OpenSSH using the following commands.</li></ol><code>&nbsp; &nbsp;Get-WindowsCapability -Online | Where-Object Name -like 'OpenSSH*'</code><code>&nbsp; &nbsp;# Install the OpenSSH Client</code><code>&nbsp; &nbsp;Add-WindowsCapability -Online -Name OpenSSH.Client~~~~0.0.1.0</code><code>&nbsp; &nbsp;# Install the OpenSSH Server</code><code>&nbsp; &nbsp;Add-WindowsCapability -Online -Name OpenSSH.Server~~~~0.0.1.0</code><code>&nbsp; &nbsp;# Start the sshd service</code><code>&nbsp; &nbsp;Start-Service sshd</code><code>&nbsp; &nbsp;# OPTIONAL but recommended:/code&gt;</code><code>&nbsp; &nbsp;Set-Service -Name sshd -StartupType 'Automatic'</code><code>&nbsp; &nbsp;# Confirm the Firewall rule is configured. It should be created automatically by setup. Run the following to verify</code><code>&nbsp; &nbsp;if (!(Get-NetFirewallRule -Name "OpenSSH-Server-In-TCP" -ErrorAction SilentlyContinue | Select-Object Name, Enabled)) {</code><code>&nbsp; &nbsp; &nbsp; &nbsp; Write-Output "Firewall Rule 'OpenSSH-Server-In-TCP' does not exist, creating it..."</code><code>&nbsp; &nbsp; &nbsp; &nbsp; New-NetFirewallRule -Name 'OpenSSH-Server-In-TCP' -DisplayName 'OpenSSH Server (sshd)' -Enabled True -Direction Inbound -Protocol TCP -Action Allow -LocalPort 22</code><code>&nbsp; &nbsp;} else {</code><code>&nbsp; &nbsp; &nbsp; &nbsp; Write-Output "Firewall rule 'OpenSSH-Server-In-TCP' has been created and exists."</code><code>&nbsp; &nbsp;}</code><ol start="2"><li>With OpenSSH installed, create a key using the following command.</li></ol><code>&nbsp; &nbsp;ssh-keygen</code>By default, the system will save the keys to <code>C:\Users\&lt;user&gt;/.ssh/id_rsa.</code><ol start="3"><li>Exchange keys using the following command.</li></ol><code>&nbsp; &nbsp;type $env:USERPROFILE\.ssh\id_rsa.pub | ssh ubuntu@&lt;board_ip&gt; "cat &gt;&gt; .ssh/authorized_keys"</code>To establish a SSH connection from Visual Studio Code, we must first install the remote SSH option from the extensions (Figure 1).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE3MTQ3NTU5NTE3LUFNRHBfZmlnMS53ZWJwIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 1: SSH remote connection application. (Source: Mouser Electronics)Once this is installed, we can connect to the AMD Kria KR260 board (Figure 2), which will allow us to develop our applications remotely in the KR260 file system.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE3MTQ3NTc0MDA4LUFNRHBfZmlnMi53ZWJwIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 2: Establishing an SSH remote connection. (Source: Mouser Electronics)To be able to use X11 forwarding, we must first install cXsrv Windows X Server (available in the Resources section) on our development machine. Run X Server and configure it. For screenshots fo this setup see <a href="https://resources.mouser.com/robotics/mastering-multi-axis-robotics-guide" target="_blank" rel="noopener noreferrer">here</a>. &nbsp;Connect to the display by running the following command in a command window on the development machine:<code>set DISPLAY=127.0.0.1:0.0</code>We can then initiate an SSH connection with the AMD Kria KR260 board and start developing our robot application.<code>ssh -Y &lt;user&gt;@&lt;board_ip&gt;</code>As this runs, the robot arm will move and you will see a visualization of this movement on X Server (Figure 7).<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzE3MTQ3Njc4MjM0LUFNRHBfZmlnNy53ZWJwIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 7: X Server robotic arm visualization (Source: Mouser Electronics)<h2 id="isPasted">Wrap Up</h2>Robotics can be complicated. In this project, we have seen that the AMD Kria™ KR260 kit can enable rapid development of robotic solutions using ROS 2. The KR260 provides the ability to accelerate features within the programmable logic element or to integrate further system control elements such as time-sensitive networking within the programmable logic.<hr>AMD, and the AMD Arrow logo, Kria, and combinations thereof are trademarks of Advanced Micro Devices, Inc. Other product names used herein are for identification purposes and may be trademarks of their respective owners.

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