TheRobotStudio/SO-ARM100
SO ARM100
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.
The project distinguishes itself through the integration of touch-sensing and flexible filaments for adaptive grasping. It also provides a dedicated imitation learning dataset tool, featuring a web interface for labeling and visualizing robotics data to train machine learning models using human demonstrations.
The system covers several operational areas, including low-cost robot fabrication, hardware configuration for motor IDs and baudrates, and a full imitation learning workflow. It also includes utilities for robot servo debugging, leader-follower teleoperation, and the creation of modular hardware accessories like camera mounts.
Features
- 3D-Printable Robot Designs - Provides 3D-printable designs and assembly guides for building affordable robotic arms.
- Open-Source Robot Arm Hardware - Provides 3D-printable designs and assembly guides for building affordable, open-source robotic arms.
- Expert Imitation Learning - Implements an imitation learning workflow using human demonstrations and pretrained models.
- Imitation and Reinforcement Learning Toolkits - Provides a pipeline to collect and label human demonstration data for training robotic policies.
- Communication Bus Calibration - Includes software to synchronize motor communication parameters and IDs via USB.
- Motor Bus Configuration - Provides a utility to assign unique identification IDs and synchronize communication baudrates for motors.
- Joint Position Synchronization - Synchronizes position values between leader and follower arms for consistent movement.
- Compliant Gripper Design - Uses flexible filament designs to create grippers capable of adapting to object shapes.
- Structural Part Fabrication - Provides printable designs and bills of materials to produce physical structural components.
- Kinematic Calibration - Includes calibration software to synchronize motor parameters and arm positions.
- Low-Cost Robot Fabrication - Provides 3D-printable designs and assembly guides for building affordable robotic arms.
- Robot Arm Calibration Software - Provides software to synchronize leader and follower arm positions and configure motor communication parameters via USB.
- Tactile Gripper Integration - Integrates touch-sensing and flexible filaments into robotic grippers for adaptive grasping.
- Touch Surface Sensing - Integrates touch-sensing capabilities into the robotic gripper for physical interaction feedback.
- Tactile Grippers - Implements hardware designs for robotic grippers that integrate touch-sensing and flexible filaments for adaptive grasping.
- Data Labeling Tools - Provides a web interface for labeling robot datasets to prepare training data for machine learning models.
- Dataset Labeling Interfaces - Provides a web interface for labeling and visualizing robotics data to facilitate human-demonstration training.
- AI Dataset Visualizers - Features a web interface for visualizing robotics telemetry and demonstration logs for interactive analysis.
- Robot Learning Platforms - Includes a tool for tagging robot demonstrations via a web interface to prepare ML training data.
- Robotics Visualization Tools - Provides interactive charts and tools for displaying and analyzing synchronized robotic performance data and demonstrations.
- Leader-Follower Teleoperation - Implements leader-follower teleoperation to sync joint positions for data collection.
- Servo Diagnostics Tools - Ships a software utility for connecting to motors via USB to program, test, and troubleshoot servo performance.
- Robot Arm Models - Description for modular, low-cost desktop robotic arms.
- Robot Arms - Low-cost 3D-printable arm for accessible end-to-end learning.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
