Waveshare UGV Beast is an off-road robot with tracked wheels designed for Raspberry Pi 4 or 5 SBC handling AI vision and strategy planning, while an ESP32 sub-controller takes care of motion control and sensor data processing. If the design feels familiar, it’s because it’s a variant of the UGV Rover unmanned ground vehicle we covered in 2024, which replaces the six wheels of the original model with two continuous tracks, as found in military tanks, for better driving in difficult terrain. Waveshare UGV Beast specifications: Supported SBCs – Raspberry Pi 4B or Raspberry Pi 5 Multi-function driver board/sub-controller Main SoC – ESP32 wireless microcontroller with WiFi, Bluetooth, ESPNOW connectivity Motor drivers – 2x TB6612FNG chips Peripheral interfaces 4x motor control connectors 2x servo connectors Lidar USB (4-pin) and UART (USB-C) connectors 2x 4-pin I2C connectors Sensor – 9-axis attitude sensor (ICM20948) for image stabilization Misc – EN and user […]
NASA Artemis Watch 2.0 – An ESP32-S3-powered, NASA-inspired wearable kit for education
CircuitMess NASA Artemis Watch 2.0 is a programmable, NASA-themed smartwatch based on an ESP32-S3 WiFi and Bluetooth module and a 1.14-inch monochrome display. The watch also features an accelerometer, a gyroscope, a buzzer, an RTC, a button, several LEDs, and a USB port for programming and charging the built-in 600 mAh battery. NASA Artemis Watch 2.0 specifications: Core module – ESP32-S3-MINI-1-N4R2 SoC – ESP32-S3 dual-core Xtensa LX7 processor with WiFi 4 and Bluetooth 5.0 connectivity Memory – 2MB PSRAM Storage – 4MB QSPI flash PCB antenna Display – Built-in 1.44-inch display USB – 1x USB Type-C port for charging and programming Sensors 6-axis LSM6DS3TR accelerometer and gyroscope Temperature sensor (TBC) Misc Lever button 6x user LEDs, 1x power LED, 1x RGB LED Buzzer RTC + backup battery Power Supply 5V via USB-C port 600 mAh LiPo battery, good for 2 to 3 hours on a charge Dimensions and Weight – […]
Velxio is an open-source, self-hosted Arduino, Raspberry Pi, and ESP32 simulator
Velxio is an open-source, self-hosted simulator for Arduino, ESP32, and Raspberry Pi boards that works directly in your web browser. You can drag-and-drop boards, connect components and modules, write and run code in Arduino or Python, and access the serial console, all without hardware. If it looks similar to what the Wokwi simulator has to offer, it’s because Velxio was inspired by it and even integrates the AVR8 CPU emulator, RP2040 emulator, and QEMU fork for ESP32 Xtensa emulation from the Wokwi project. But the key difference is that Velxio can be self-hosted, although there’s also an online demo. Velxio currently supports 19 targets across five architectures AVR8 (ATmega / ATtiny) Arm Cortex-M0+ (Raspberry Pi RP2040) RISC-V RV32IMC/EC (ESP32-C3 / CH32V003) Xtensa LX6/LX7 (ESP32 / ESP32-S3 via QEMU) Arm Cortex-A53 (Raspberry Pi 3 Linux via QEMU) The project also offers 48 components. The developer mentions that additional features compared to […]
Hugging Face’s Reachy Mini is an open-source AI robot for your computer or Raspberry Pi CM4
Better known for its artificial intelligence software solutions, Hugging Face unveiled the Reachy Mini open-source desktop robot last year. It is designed to deploy AI applications that interface with the physical world. The robot features a camera, four microphones, and a speaker, and can move its 6 DoF (degrees of freedom) head, rotate its body, or wave its antennas thanks to nine servo motors. Two versions are available: the Reachy Mini Lite designed for computers running Mac, Linux, and Windows, and the Reachy Mini Wireless autonomous robot, powered by a Raspberry Pi CM4, adding WiFi and Bluetooth connectivity, an accelerometer, and battery support. Both models share most of the same specifications: Reachy Mini’s SDK can be found on GitHub. It’s based on Python, but also supports JavaScript and Web apps, and can integrate with LLMs to easily build apps and publish them to Hugging Face. The SDK also features several […]
MediaTek unveils 50 TOPS Genio Pro 5100 Cortex-X925/X4/A720 SoC, 7.2 TOPS Genio 420 Cortex-A78/A55 SoC for AIoT applications
After launching the Genio 360/360P hexa/octa-core SoCs last month, MediaTek has now expanded the lineup with the Genio Pro 5100 and Genio 420 AIoT SoCs at Embedded World 2026. The Genio Pro 5100 is a 3nm SoC with an “all big-core” architecture and a 50+ TOPS NPU for Edge AI applications. The Genio 420, on the other hand, is a cost-efficient 6nm platform designed for smart home, retail, and industrial IoT devices. MediaTek Genio Pro 5100 The Genio Pro 5100 integrates one Cortex-X925, three Cortex-X4, and four Cortex-A720 cores, as well as an Arm Immortalis-G925 GPU, and supports LPDDR5X memory up to 8533 Mbps. It can handle up to three 4K displays, up to 16 cameras via virtual channels, and 8K30 video encode/decode, and offers interfaces such as PCIe Gen4, USB 3.2 Gen2, USB 2.0, and dual 2.5GbE MAC. Genio Pro 5100 (MT8894) specifications: CPU – 8-core Arm v9.2 processor […]
Arduino Matter Discovery Bundle educational kit combines Arduino Nano Matter with three Modulino modules
Arduino has just announced the Arduino Matter Discovery Bundle (AKX00081), an all-in-one development kit designed to help users learn, prototype, and build Matter-over-Thread smart home devices quickly. The kit is based on the Arduino Nano Matter development board and works with the Matter ecosystem, including compatible platforms such as Apple HomeKit, Google Home, Amazon Alexa, and Home Assistant. The bundle also includes a Nano Connector Carrier with Grove and Qwiic interfaces, a microSD slot, and various IO options. The kit features three Qwiic-based Modulino nodes, namely a Latch Relay, a Distance module for presence detection, and a Thermo module for temperature and humidity sensing. Arduino Matter Discovery Bundle specifications: Main board – Arduino Nano Matter MCU – SiLabs MGM240SD22VNA MCU core – 32-bit Arm Cortex-M33 with DSP (digital signal processing) instruction and FPU (floating-point unit) @ 78 MHz Storage/Memory – 1536 KB flash program memory, 256 KB RAM data memory […]
MediaTek Genio 360/360P hexa/octa-core Cortex-A76/A55 AIoT SoC features 8 TOPS NPU for cost-sensitive embedded applications
MediaTek Genio 360 and Genio 360P are respectively hexa-core and octa-core Arm Cortex-A76/A55 AIoT processors featuring a MediaTek NPU delivering up to 8 TOPS of AI performance, and designed for cost-sensitive embedded applications. The chips support up to 8GB of memory and eMMC 5.1, SPI NOR, and SD 3.0 storage interfaces. They feature two 4-lane MIPI DSI and one 4-lane DP/eDP interfaces for single or dual display setups, two 4-lane MIPI CSI camera interfaces, audio inputs/outputs, Gigabit Ethernet with TSN, optional WiFi 5 and Bluetooth 5.3 via MT6631N, USB 3.1 and USB 2.0 interfaces, PCIe Gen2 x1, and low-speed interfaces. MediaTek Genio 360/360P specifications: CPU MediaTek Genio 360 (MT8366) – Hexa-core processor 1x Arm Cortex-A76 core clocked at up to 1.9 GHz (industrial) / 2.0GHz (commercial) 5x Arm Cortex-A55 cores clocked at up to 1.7 GHz (industrial) / 2.0GHz (commercial) MediaTek Genio 360P (MT8367) – Octa-core processor 2x Arm Cortex-A76 […]
DShanPi-A1 AI Education Rockchip RK3576 SBC features HDMI input and output ports, dual GbE
DshanPi-A1 AI Education is a single board computer (SBC) powered by a Rockchip RK3576 octa-core Cortex-A72/A53 SoC, and paired with up to 8GB RAM and 64GB eMMC flash, which I first discovered in the Linux 6.19 changelog. The board features HDMI 2.1 video output, a mini HDMI video input port, a MIPI DSI display interface, two MIPI CSI connectors for up to four cameras, dual GbE, an M.2 Key-E socket for WiFi and Bluetooth, a few USB ports, and a 40-pin GPIO header compatible with some Raspberry Pi HAT boards. DShanPi-A1 specifications: SoC – Rockchip RK3576 CPU – Octa-core CPU with 4x Cortex-A72 cores at 2.2 GHz, 4x Cortex-A53 cores at 2.0 GHz (1.6GHz for Industrial and Automotive) GPU – Arm Mali-G52 MC3 GPU with support for OpenGL ES 1.1, 2.0, and 3.2, OpenCL 2.0, and Vulkan 1.2 NPU – 6 TOPS (INT8) AI accelerator with support for INT4, INT8, […]








