TRACEPaw sensorized paw helps legged robots “feel the floor” with Arduino Nicla Vision

TRACEPaw

Our four-legged friends don’t walk on tarmac the same way as they do on ice or sand as they can see and feel the floor with their eyes and nerve endings and adapt accordingly. The TRACEPaw open-source project, which stands for “Terrain Recognition And Contact force Estimation through Sensorized Legged Robot Paw“, aims to bring the same capabilities to legged robots. Autonomous Robots Lab achieves this through the Arduino Nicla Vision board leveraging its camera and microphone to run machine learning models on the STM32H7 Cortex-M7 microcontroller in order to determine the type of terrain and estimate the force exercized on the leg. But the camera is apparently not used to look at the terrain, but instead, at the deformation of the silicone hemisphere – made of “Dragon Skin” – at the end of the leg to estimate 3D force vectors, while the microphone is used to recognize terrain types […]

Tiny solder-down NXP i.MX 93 System-on-Module powers credit card-sized evaluation board

Raspberry Pi NXP i.MX 93 SBC

Ka-Ro Electronics’ QS93 is a tiny solder-down NXP i.MX 93 System-on-Module (SoM) running Linux and designed for edge processing. The company also offers a credit card-sized evaluation board that may remind some of the Raspberry Pi with its GPIO header and general layout, but it comes with two Fast Ethernet ports and one USB 2.0 port. We’ve already covered several system-on-modules based on the NXP i.MX 93 Cortex-A55/M33 AI processor including some with high-density board-to-board connectors such as the Compulab UCM-IMX93 and Forlinx FET-MX9352-C, others with a SO-DIMM connector like the VAR-SOM-MX93, and finally some designed to be soldered on the carrier board such as the OSM-L compatible iW-RainboW-G50M, and the QS93 adds to the latter category in a tiny 27×27 mm form factor. Ka-Ro electronics QS93 specifications: SoC – NXP i.MX 93 with CPU – Up to dual-core Cortex-A55 processor @ up to 1.5 GHz Real-time core – Arm […]

MediaPipe for Raspberry Pi released – No-code/low-code on-device machine learning solutions

MediaPipe Studio Raspberry Pi 4

Google has just released MediaPipe Solutions for no-code/low-code on-device machine learning for the Raspberry Pi (and an iOS SDK) following the official release in May for Android, web, and Python, but it’s been years in the making as we first wrote about the MediaPipe project back in December 2019. The Raspberry Pi port is an update to the Python SDK and supports audio classification, face landmark detection, object detection, and various natural language processing tasks. MediaPipe Solutions consists of three components: MediaPipe Tasks (low-code) to create and deploy custom end-to-end ML solution pipelines using cross-platform APIs and libraries MediaPipe Model Maker (low-code) to create custom ML models MediaPipe Studio (no-code) webpage to create, evaluate, debug, benchmark, prototype, and deploy production-level solutions. You can try it out directly in your web browser at least on PC and I could quickly test the object detection on Ubuntu 22.04. MediaPipe Tasks can be […]

ESP32-S3 based Arduino Nano ESP32 board supports Arduino and MicroPython programming

Arduino Nano ESP32

The Arduino Nano ESP32 is an ESP32-S3-based WiFi and Bluetooth microcontroller board designed for IoT applications for hobbyists and enterprise use cases. The new Nano board comes with 8 MB  PSRAM and 16 MB flash storage and can be programmed with either the Arduino or MicroPython languages. It’s not the first ESP32 board from Arduino, as the Nano RP2040 Connect pairs a Raspberry Pi RP2040 MCU with an ESP32 module from u-Blox and the just-released Arduino UNO R4 WiFi marries a Renesas RA4M1 Arm Cortex-M33 MCU with an ESP32-S3-MINI-1 module. But the Arduino Nano ESP32 is different since it’s the first ESP32 board from Arduino where the Espressif chip is the only microcontroller onboard and handles both wireless connectivity and GPIOs. Arduino Nano ESP32 specifications: Wireless module – u-Blox NORA-W106-10B with MCU –  ESP32-S3 dual-core Xtensa LX7 microcontroller @ up to 240 MHz with vector extensions, 512KB SRAM, 384KB ROM, […]

Particle launches Photon 2 Realtek RTL8721DM dual-band WiFi and BLE IoT board, Particle P2 module

Particle Photon 2

Particle has launched the Photon 2 dual-band WiFi and BLE IoT board powered by a 200 MHz Realtek RTL8721DM Arm Cortex-M33 microcontroller, as well as the corresponding Particle P2 module for integration into commercial products. The original “Spark Photon” WiFi IoT board was launched in 2014 with an STM32 MCU and a BCM43362 wireless module, but the market and company name have changed since then, and Particle has now launched the Photon 2 board and P2 module with a more modern Cortex-M33 WiFi & BLE microcontroller with support for security features such as Arm TrustZone. Particle Photon 2 specifications: Wireless MCU – Realtek RTL8721DM CPU – Arm Cortex-M33 core @ 200 MHz Memory – 4.5MB embedded SRAM of which 3072 KB (3 MB) is available to user applications Connectivity – Dual-band WiFi 4 up to 150Mbps and Bluetooth 5.0 Security Hardware Engine Arm Trustzone-M Secure Boot SWD Protection Wi-Fi WEP, […]

i-Pi SMARC 1200 (MediaTek Genio 1200) devkit tested with a Yocto Linux image

i-Pi SMARC 1200 Yocto Linux glmark2 benchmark

Last weekend I received ADLINK’s i-Pi SMARC 1200 development kit powered by MediaTek Genio 1200 Octa-core Cortex-A78/A55 AIoT processor, checked out the hardware and wanted to install the Yocto Linux image but stopped in my tracks because it looked like I had to install Ubuntu 18.04 first in a Virtual Machine or another computer. But finally, the documentation has been updated to clarify “Ubuntu 18.04 or greater” is required, and I had no problem flashing the image from a Ubuntu 22.04 laptop after installing dependencies and tools as follows:

That’s it for the tools. Eventually, the development kit will support three images: Yocto Linux, Android 13 (July 2023), and Ubuntu 20.04 (Q3 2023). So that means only the Yocto Linux image is available from the download page at this time, and that’s what I’ll be using today. We’ll need to connect the micro USB to USB cable between the […]

CompuLab UCM-iMX93 – A miniature NXP i.MX 93 module with WiFi 5 & Bluetooth 5.3

Compulab UCM-iMX93 system-on-module

CompuLab UCM-iMX93 is a miniature system-on-module powered by the new NXP i.MX93 Cortex-A55 AI processor family with up to 2GB RAM and 64GB eMMC flash. The tiny 38x28mm features a Gigabit Ethernet PHY, a WiFi 5 and Bluetooth 5.3 wireless modules, and plenty of multimedia, communication, and peripheral interfaces through two 100-pin high-density connectors including display and camera interfaces, USB ports, CAN FD, and up to 79 GPIOs. UCM-iMX93 specifications: SoC – NXP i.MX9352 or i.MX9331 dual-core/single-core Arm Cortex-A55 @ 1.5 GHz (industrial) / 1.7 GHz (commercial) with Arm Cortex-M33 real-time core @ 250 MHz, Arm Ethos U65 microNPU System Memory – 512MB to 2GB LPDDR4 Storage – 8GB to 64GB eMMC flash Networking Gigabit Ethernet PHY Certified WiFi 5 (802.11ac) and Bluetooth 5.3 BLE module (NXP 88W8997) 2x 100-pin 0.4mm pitch high-density UCM connectors Display 4-lane MIPI-DSI up to 1920 x 1080 @ 60Hz 4-lane LVDS up to 1366 […]

FireBeetle 2 ESP32-S3 camera board ships 16MB flash, 8MB PSRAM, PCB or external antenna

FireBeetle 2 ESP32-S3 camera board

DFRobot “FireBeetle 2 ESP32-S3” is a 2MP camera board with ESP32-S3N16R8 dual-core WiFi and Bluetooth microcontroller fitted with 16MB flash and 8MB PSRAM, and offered in two versions: a more compact variant with a PCB antenna, and one with an external antenna offering a better signal quality. The FireBeetle 2 ESP32-S3 also features two rows of I/Os with GPIO, I2C, SPI, ADC, USB 2.0, etc…, a USB-C port for power and programming, a few buttons, and support for a LiPo battery through a 2-pin JST connector and a charging circuit. FireBeetle 2 ESP32-S3 specifications: ESP32-S3-WROOM-1 wireless module SoC –  ESP32-S3FN16R8 dual-core Tensilica LX7 microcontroller @ 240 MHz with 2.4 GHz 802.11n WiFI 4 and Bluetooth 5.0 LE connectivity Memory – 8MB PSRAM Storage – 16MB SPI flash Camera – Camera connector fitted with 2MP OV2640 camera with 68° FoV, up to 1600×1200 resolution Display – GDI connector for optional 1.54-inch, […]

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