openmv

Posted on by Jean-Luc Aufranc (CNXSoft) - 119 Comments on Giveaway Week 2024 – RT-Thread Vision board with Renesas RA8D1 Arm Cortex-M85 MCU

Giveaway Week 2024 – RT-Thread Vision board with Renesas RA8D1 Arm Cortex-M85 MCU

RT-Thread Vision board

It’s already Friday, and the fifty prize of CNX Software’s Giveaway Week 2024 will be the RT-Thread Vision board equipped with a Renesas RA8D1 Arm Cortex-M85 microcontroller, a camera, an optional LCD display, and a 40-pin GPIO header. The board is used as an evaluation platform for the Renesas RA8D1 MCU and RT-Thread real-time operating system. As its name implies, it’s mainly designed for computer vision applications leveraging the Helium MVE (M-Profile Vector Extension) for digital signal processing (DSP) and machine learning (ML) applications. I haven’t reviewed it myself and instead, received two samples from RT-Thread who sent them to me by mistake, so I’ll give them away here and on the Thai website. But it was reviewed by Supachai who tested the RT-Thread Vision board with OpenMV and ran a few benchmarks last June. The Helium MVE did not seem to be utilized in OpenMV at that time (June […]

Posted on by Supachai Vorapojpisut - 1 Comment on RT-Thread Vision board review – Part 1: OpenMV on Renesas RA8D1 Cortex-M85 microcontroller

RT-Thread Vision board review – Part 1: OpenMV on Renesas RA8D1 Cortex-M85 microcontroller

RT-Thread VIsion board vs WeAct STM32H743

I am always interested in real-time operating systems (RTOS) for microcontrollers (MCUs) with my past backgrounds in µC/OS-II, mbed, and FreeRTOS. When the opportunity arose to get my hands on the RT-Thread Vision Board, thanks to the RT-Thread team and CNX Software, I was excited to check it out. This board, a collaboration between RT-Thread and Renesas, packs a powerful Renesas RA8D1 Cortex-M85 MCU and comes pre-loaded with OpenMV firmware. OpenMV’s MicroPython engine lets you jump right into embedded vision development, perfect for experimenting with computer vision tasks. But the real power lies in RT-Thread’s ability to handle tasks very quickly, which we’ll explore with C/C++ development in part two. This first part will focus on getting you familiar with the hardware using the OpenMV firmware, making it a smooth entry point for beginners. Plus, I have a collection of other Renesas evaluation boards, so you can bet I’ll be […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 3 Comments on WeAct STM32H743 Arm Cortex-M7 board ships with a 0.96-inch LCD and a choice of camera sensors

WeAct STM32H743 Arm Cortex-M7 board ships with a 0.96-inch LCD and a choice of camera sensors

WeAct STM32H7 LCD camera development board

WeAct STM32H743 is a small MCU development board powered by a 480 MHz STMicro STM32H743VIT6 Cortex-M7 microcontroller and equipped with a small LCD and a camera connector taking OV2640, OV5640-AF, OV7670, or OV7725 camera sensors. The board comes with 2048KB flash and 1MB RAM built into the STM32H7 microcontroller, 8MB SPI flash, 8MB QSPI flash, a microSD for data storage,  USB-C port for power and programming, a few buttons, and plenty of I/Os accessible through two 44-pin headers. WeAct STM32H743 specifications: MCU – STMicro STM32H743VIT6 Arm Cortex-M7 microcontroller at 480MHz with FPU, DSP, and MPU, 2048KB flash, 1MB RAM Storage – 8MB SPI Flash, 8MB QSPI Flash (bootable), microSD card socket Display – 0.96-inch TFT LCD based on ST7735 SPI display driver Camera 8-bit Digital Camera Interface (DCMI) with autofocus support OV2640 (1600×1200), OV5640-AF (2592×1944 with autofocus), OV7670 (640×480), or OV7725 (640×480) camera sensors are supported USB – 1x USB-C […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 1 Comment on TRACEPaw sensorized paw helps legged robots “feel the floor” with Arduino Nicla Vision

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 […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 9 Comments on Arduino Nicla Vision – A tiny STM32H7 board with 2MP camera, WiFi & Bluetooth LE, sensors

Arduino Nicla Vision – A tiny STM32H7 board with 2MP camera, WiFi & Bluetooth LE, sensors

Arduino Nicla Vision

Arduino Nicla Vision is an ultra-compact (~2.3×2.3 cm) board powered by an STMicro STM32H7 dual-core Cortex-M7/M4 microcontroller, and equipped with a 2MP camera, a WiFi & Bluetooth LE module, and a few sensors. Those features make the board suitable for machine vision and edge computing applications such as asset tracking, image detection, object recognition, and predictive maintenance. For instance, image detection, facial recognition, automated optical inspection, vehicle plate reading, or gesture recognition can be added to projects, either using Nicla Vision as a standalone board or in combination with Portenta or MKR boards. Arduino Nicla Vision specifications: Microcontrollers – STMicro STM32H757AII6 dual-core MCU with Arm Cortex M7 @ 480MHz, Cortex-M4 @ 240MHz, 2 MB flash, 1MB RAM Storage – 16MB QSPI flash Connectivity – 2.4GHz WiFi 802.11b/g/n up to 65 Mbps and Bluetooth 5.1 BR/EDR/LE via Murata 1DX module Camera – 2MP GC2145 color camera. USB – Micro USB port […]

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