SO-ARM100 is an open-source robot arm hardware project providing 3D-printable designs and assembly guides for building affordable robotic arms. It includes calibration software to synchronize motor communication parameters and arm positions via USB, alongside hardware designs for tactile sensing robotic grippers.
Die Hauptfunktionen von therobotstudio/so-arm100 sind: 3D-Printable Robot Designs, Open-Source Robot Arm Hardware, Expert Imitation Learning, Imitation and Reinforcement Learning Toolkits, Communication Bus Calibration, Motor Bus Configuration, Joint Position Synchronization, Compliant Gripper Design.
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This project provides a complete set of design files and hardware specifications for a 3D-printable industrial-style robot arm. The system includes a CAN bus robot controller for managing stepper motors and sensors, a kinematics engine for calculating joint angles and poses, and a UDP-based Python API for sending motion commands and monitoring telemetry. The system features a force-controlled robotic gripper that utilizes field-oriented control on stepper motors to enable compliant grasping and precise force sensing. It also includes a 3D position visualization tool for real-time telemetry tr
This project is a comprehensive research platform designed for the end-to-end lifecycle of robotic learning. It provides a modular framework for training neural network policies—specifically through imitation and reinforcement learning—and deploying them onto physical robotic hardware. By offering a unified interface for hardware abstraction, the platform decouples high-level control logic from the specific sensors and actuators of diverse robotic systems. The framework distinguishes itself through a standardized approach to data and policy management. It utilizes a consistent schema for reco
Legged Gym is a high-performance simulation platform and toolkit engineered for training autonomous robotic agents in complex, physics-based environments. It provides a comprehensive framework for developing legged locomotion control policies, enabling robots to learn movement strategies for navigating uneven terrain and managing physical disturbances through reinforcement learning. The platform distinguishes itself by utilizing hardware-accelerated physics and headless execution to maximize computational throughput during training. It incorporates a domain randomization pipeline that injects
XLeRobot is an embodied AI robotics platform and hardware ecosystem designed for developing and deploying autonomous robots. It integrates a dual-arm mobile robot platform with an LLM-based robot controller, a physics-based simulation environment, and a teleoperation interface to translate natural language instructions into physical actions. The project emphasizes low-cost robot fabrication using 3D printing and affordable components to create a mobile base with interchangeable arms and grippers. It features a specialized teleoperation workflow that allows for remote hardware control via VR i