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HOVER
Overview :
HOVER is a multi-functional neural full-body controller designed for humanoid robots. It provides universal motion skills by imitating full-body movements and learns various full-body control modes. HOVER integrates different control modes into a unified strategy through a multi-modal policy distillation framework, enabling seamless transitions between different control modes while retaining each mode's unique advantages. This controller enhances the control efficiency and flexibility of humanoid robots across multiple modes, offering a robust and scalable solution for future robotic applications.
Target Users :
The target audience is researchers and developers in robotics, particularly professionals focused on humanoid robot control and motion planning. HOVER provides a unified framework for handling various control tasks, enabling researchers to develop and deploy humanoid robots more efficiently, while minimizing the need to retrain models for different tasks.
Use Cases
Example 1: Using the HOVER controller for navigation tasks in humanoid robots, achieving precise tracking of the robot's root velocity.
Example 2: In desktop manipulation tasks, the HOVER controller prioritizes tracking the upper body joint angles to perform fine operations.
Example 3: Achieving seamless mode switching in humanoid robots using the HOVER controller, such as transitioning from navigation mode to manipulation mode.
Features
- Multi-modal policy distillation framework: Integrates various control modes into a unified strategy.
- Seamless mode switching: Smooth transitions between different control modes while maintaining their advantages.
- Enhanced control efficiency: Eliminates the need to retrain strategies for each control mode.
- Flexibility and scalability: Suitable for a wide range of robotic application scenarios.
- DAgger-based optimization: Uses supervised learning to optimize Oracle actions, improving consistency between student and Oracle strategies.
- Supports multiple command spaces: Includes motion position tracking, local joint angle tracking, and root tracking.
- Adapts to various tasks: Such as navigation, hand manipulation, and desktop operations, each requiring different control modes.
How to Use
1. Visit the HOVER project webpage to download the relevant code and documentation.
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2. Configure the environment and install the necessary dependencies following the documentation.
3. Understand HOVER's multi-modal policy distillation framework and adjust parameters as needed.
4. Utilize the provided sample code to simulate or practically test robotic control tasks.
5. Optimize policies using the DAgger method to improve control performance.
6. Choose an appropriate control mode based on the actual application scenario and make corresponding configurations.
7. Deploy the HOVER controller on a real humanoid robot and conduct debugging and optimization.
8. Further refine and enhance the control strategy based on feedback and performance evaluation.
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