MarkFzp/mobile-aloha
Mobile Aloha
Mobile Alohas is a bimanual mobile manipulation framework designed to learn whole-body robot control. It provides an integrated imitation learning pipeline that manages the process of collecting human demonstration data and training behavior models to automate complex physical tasks.
The system features a robotic teleoperation interface that maps human movements to a mobile robot with dual arms. It includes a whole-body motion dataset tool used for recording, visualizing, and replaying joint and sensor data from manipulation sessions.
The framework covers several capability areas, including whole-body teleoperation, imitation learning training, and bimanual robot manipulation. It also provides tools for recorded data visualization and hardware movement replay.
Features
- Dual-Arm Mobile Robots - Provides a framework for controlling a robotic platform combining a wheeled base with two arms.
- Behavioral Cloning Toolkits - Trains behavior models using human demonstration data to automate complex physical movements.
- Imitation Learning Pipelines - Implements a workflow for collecting human demonstration data and training behavior models.
- Policy Execution Engines - Runs trained behavior models to autonomously generate control commands based on live sensory input.
- Imitation Learning Trainings - Trains neural networks to map sensor inputs to robot actions using human demonstration data.
- Teleoperated Demonstration Collection - Captures high-dimensional movement data by mapping human controllers to a remote robot in real time.
- Bimanual Mobile Manipulation Frameworks - Provides a complete framework for learning whole-body robot control through human teleoperation and imitation learning.
- Teleoperation Systems - Ships a remote control system that maps human movements to a mobile robot with dual arms.
- Demonstration Collection Systems - Captures and structures sensor and joint data from human operators for machine learning datasets.
- Bimanual Coordination - Implements unified control and learning for synchronized dual-arm and mobile base movements.
- Whole-Body Teleoperation - Enables real-time remote control of the mobile robot's entire body and arms using a master device.
- Bimanual Capture - Records human demonstrations of dual-arm and base movements for bimanual robotic learning.
- Mobile Base Capture - Captures whole-body human movements via a remote interface to create imitation learning datasets.
- Robotic Motion Dataset Tools - Provides a utility for recording, visualizing and replaying joint and sensor data from manipulation sessions.
- Hardware Movement Replays - A functionality that executes previously saved episodes by sending stored movement commands back to the physical hardware.
- Robotics Visualization Tools - Provides tools for reviewing and rendering recorded sensor data and physical episodes.
- Robotic State Logging - Saves timestamped robotic joint angles and sensor readings into structured files for dataset generation.
- Data Stream Recording and Replay - Provides capabilities to stream saved joint commands back to physical hardware for episode replay.
- Robotics Data Recording - Captures and saves joint and sensor information during sessions into structured files.
Star history
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