FrodoBots Lab is a GitHub organization focused on robotics projects, including SDKs for earth rovers, teleoperation devices, and web interfaces for robots. They also work with kernel development and AI for robotics.
MentorPi is a robot car platform powered by the Raspberry Pi 5 and compatible with ROS2, offering options for Mecanum or Ackermann chassis. It includes features like obstacle avoidance, line tracking, and SLAM capabilities, making it suitable for robotics education and development.
A STEAM education robot that makes teaching and learning robot programming simple and fun, featuring advanced programmable capabilities, 160+ mechanical parts, and the ability to build 10 different configurations.
Introduction to the OSOYOO V4.0 Robot Car for Raspberry Pi, highlighting its advanced features and capabilities for complex robotic projects compared to Arduino-based kits.
Edison is a programmable robot designed to be a complete STEM teaching resource for coding and robotics education for students from 4 to 16 years of age. Edison empowers students to become not just coders, but inventors, problem solvers, and creative thinkers.
3D simulations and movement control with PyBullet. This article demonstrates how to build a 3D environment with PyBullet for manually controlling a robotic arm, covering setup, robot loading, movement control (position, velocity, force), and interaction with objects.
Nvidia has expanded its Jetson lineup with the Jetson AGX Thor Developer Kit, a compact platform that carries the new Jetson T5000 system-on-module. Marketed as a developer system, the dimensions and form factor place it firmly in the realm of a mini PC, although its design and purpose align more with edge AI deployment than home computing.
The Earth Rovers SDK allows users to control and monitor Frodobots Earth Rovers bots, providing endpoints for bot control, data retrieval, video streaming, mission management, and intervention handling.
This article discusses the challenges of assembly planning in manufacturing, highlighting its complexity and the need for AI-powered solutions. It explains the gap between 'as-designed' and 'as-manufactured' views of a product and how AutoAssembler aims to bridge this gap with a 'virtual build' approach. It details why classic approaches to assembly planning have stalled and how recent advancements in compute power, AI, and data models are making industrial-scale assembly planning tractable.
This post explores how developers can leverage Gemini 2.5 to build sophisticated robotics applications, focusing on semantic scene understanding, spatial reasoning with code generation, and interactive robotics applications using the Live API. It also highlights safety measures and current applications by trusted testers.
