Waveshare has recently launched the RoArm-M2-S and RoArm-M2-Pro ESP32 robotic arms with four degrees of freedom, or 4-DOF for short. The main difference is that the RoArm-M2-S is equipped with standard servos, while the RoArm-M2-Pro features all-metal ST3235 bus servos, adding more durability and performance. Designed for educational and robotics applications, the 4-DOF RoArm-M2 is sturdy yet lightweight, built using carbon fiber and aluminum alloy. It can handle payloads up to 0.5kg and has a workspace diameter of 1 meter. The arm offers high precision with a 12-bit magnetic encoder and dual-drive technology for improved torque and stability. On top of that, it features a 12-bit magnetic encoder and dual-drive technology for improved torque and stability. Other features include a 360° omnidirectional base and support for both wireless (WiFi, ESP-NOW) and wired (USB) control. These features make this device suitable for various applications including industrial automation, education, research, and DIY robotics projects. Waveshare […]
Mercury X1 wheeled humanoid robot combines NVIDIA Jetson Xavier NX AI controller and ESP32 motor control boards
Elephant Robotics Mercury X1 is a 1.2-meter high wheeled humanoid robot with two robotic arms using an NVIDIA Jetson Xavier NX as its main controller and ESP32 microcontrollers for motor control and suitable for research, education, service, entertainment, and remote operation. The robot offers 19 degrees of freedom, can lift payloads of up to 1kg, work up to 8 hours on a charge, and travel at up to 1.2m/s or about 4.3km/h. It’s based on the company’s Mercury B1 dual-arm robot and a high-performance mobile base. Mercury X1 specifications: Main controller – NVIDIA Jetson Xavier NX CPU – 6-core NVIDIA Carmel ARM v8.2 64-bit CPU with 6MB L2 + 4MB L3 caches GPU – 384-core NVIDIA Volta GPU with 48 Tensor Cores AI accelerators – 2x NVDLA deep learning accelerators delivering up to 21 TOPS at 15 Watts System Memory – 8 GB 128-bit LPDDR4x @ 51.2GB/s Storage – 16 […]
MentorPi is a ROS2-compatible, Raspberry Pi 5-based robot car with Mecanum or Ackermann chassis
MentorPi is a ROS2-compatible robot car powered by the Raspberry Pi 5, designed for AI-driven robotics and Python programming. It offers two chassis options: MentorPi-M1, which features a Mecanum-wheel chassis, and MentorPi-A1, equipped with an Ackermann chassis. Both variants come with high-performance components such as closed-loop encoder motors, STL-19P TOF lidar, 3D depth cameras, and high-torque servos. These enable precise navigation, SLAM mapping, path planning, and dynamic obstacle avoidance, making MentorPi an ideal platform for robotics tasks. The system utilizes a dual-controller architecture to optimize performance. The Raspberry Pi 5 handles AI vision processing and strategic functions, while Hiwonder’s RRC Lite expansion board manages motion control and sensor data processing. This task distribution enhances efficiency in machine vision, AI-powered navigation, and robotic control, allowing MentorPi to tackle complex AI and vision-based applications with ease. MentorPi also supports advanced features like 3D visual mapping and YOLOv5-based object detection for recognizing road […]
MIKRIK V2 Robot Car is an entry-level, open-source robotics kit built for ROS and 3D computer vision
The MIKRIK V2 Robot Car is an open-source robotics kit for studying 3D computer vision and is compatible with both ROS1 and ROS2 software suites. The two-wheel-drive robot is powered by a Raspberry Pi 4 Model B (as a ROS1 differential drive controller) and a more powerful x86 or ARM single-board computer that can support ROS2 applications like the LattePanda Delta 3, Intel NUC, or NVIDIA Jetson Nano. The robot car uses the Intel Realsense D435i camera for 3D depth vision. It is a less expensive alternative to the iRobot Create, Husarion, and TurtleBot, and compares favorably with NVIDIA’s open-source JetBot AI robot platform. The robot car’s chassis is squared-off and made from shatterproof flex plastic. The CAD files are available on GitHub for self-assembly using a laser cutter and a 3D printer. The assembly and setup process is documented on the Hackster project page. On the software end, it […]
High Torque Robotics Mini π is a bipedal robot powered by an Orange Pi 5 SBC
High Torque Robotics’ Mini π is a 54cm high bipedal robot that can walk and dance with two legs and leverages the Orange Pi 5 SBC’s features such as the 6 TOPS AI accelerator in the Rockchip RK3588S processor. The robot offers 12 degrees of freedom (DOF) and can run, jump, and even flip thanks to its twelve join motors that were developed by the company. The Mini π is designed for locomotion algorithm research and education and supports ZMP (zero moment point), MPC (Model Predictive Control), reinforcement learning locomotion control algorithms, and ROS SLAM navigation features. Mini π bipedal robot highlights: SBC – Orange Pi 5 RK3588S single board computer Controller – Custom-design “high-performance underlying controller” using 4x CAN FD communication DOF – 6 DoF per leg, or 12 in total Joint motors 8x HTDM-5047-36-NE with gear ratio: 36, 16Nm peak torque 4x HTDM-4438-32-NW with gear ratio: 32, […]
XGO-Rider is a 2-wheel self-balancing robot with an ESP32 controller plus either a Raspberry Pi CM4 or BBC Micro:bit (Crowdfunding)
XGO-Rider is a two-wheel self-balancing robot with an ESP32 controller for motor and servo control, USB-C charging, etc… and a choice between a Raspberry Pi CM4 module or a BBC Micro:bit board for display, audio, and camera (CM4-only). It’s not the first robot from Luwu Intelligence, since the company launched the XGO-Mini robot dog in 2021, followed by the XGO 2 Raspberry Pi CM4-powered desktop robotic dog with an arm which we reviewed last year. The new XGO-Rider builds on these earlier models but in a different form factor moving from four-legged robots to a 2-wheel self-balancing robot design with many of the same features including AI vision running on the Raspberry Pi CM4. XGO-Rider specifications: Host controller (one or the other) Raspberry Pi CM4 with 2GB RAM + ESP32 for main control, USB-C charging port, DIP switch BBC Micro:bit V2 + ESP32 for main control, USB-C charging port, DIP […]
EmbedFire LubanCat 4 card computer – A Rockchip RK3588S dev board with a mini PCIe socket for WiFi or 4G LTE
Launched by Yehuo Electronic EmbedFire LubanCat 4 card computer or LubanCat 4 in short, is a Rockchip RK3588S SBC that packs quite a lot of features in an 85x56mm form factor with Ethernet, USB, mini PCIe, HDMI 2.1, SIM & microSD card holder, and more. The board comes with up to 16GB of RAM and 128GB of eMMC flash. It comes with a Gigabit Ethernet port, five USB ports (including one USB-C), a built-in microphone, multiple audio inputs and outputs, a 40-pin Raspberry Pi compatible expansion header, and supports HDMI input through an adapter connected to a MIPI CSI port. EmbedFire LubanCat 4 card computer specifications: SoC – Rockchip RK3588S CPU – Octa-core processor with 4x Cortex-A76 cores @ up to 2.2-2.4 GHz, 4x Cortex-A55 cores @ up to 1.8 GHz GPU – Arm Mali-G610 GPU with OpenGL ES 3.2, OpenCL 2.2, and Vulkan 1.2 support VPU – 8Kp60 video decoder […]
myAGV 2023 four-wheel mobile robot ships with Raspberry Pi 4 or Jetson Nano
Elephant Robotics myAGV 2023 is a 4-wheel mobile robot available with either Raspberry Pi 4 Model B SBC or NVIDIA Jetson Nano B01 developer kit, and it supports five different types of robotic arms to cater to various use cases. Compared to the previous generation myAGV robot, the 2023 model is fitted with high-performance planetary brushless DC motors, supports vacuum placement control, can take a backup battery, handles large payloads up to 5 kg, and integrates customizable LED lighting at the rear. myAGV 2023 specifications: Control board Pi model – Raspberry Pi 4B with 2GB RAM Jetson Nano model – NVIDIA Jetson Nano B01 with 4GB RAM Wheels – 4x Mecanuum wheels Motor – Planetary brushless DC motor Maximum linear speed – 0.9m/s Maximum Payload – 5 kg Video Output Pi model – 2x micro HDMI ports Jetson Nano model – HDMI and DisplayPort video outputs Camera Pi model – […]