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Attitude Trajectory Optimization to Ensure Balance Hexapod Locomotion
Chen Chen1, Wei Guo1, Pengfei Wang1
1State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China.
Sensors (Basel, Switzerland)
|November 10, 2020
Summary
This study introduces a simple attitude trajectory optimization method to improve the walking balance of large hexapod robots. The method enhances environmental adaptability and simplifies control system design for robots navigating diverse terrains.
Area of Science:
- Robotics
- Control Systems Engineering
- Mechatronics
Background:
- Large-size hexapod robots require robust balance control for stable locomotion on varied outdoor terrains.
- Existing balance motion controllers can be complex and may not fully address environmental adaptability.
Purpose of the Study:
- To propose and validate a simplified attitude trajectory optimization method for enhancing the walking balance of large hexapod robots.
- To improve the robot's environmental adaptability and simplify control system design.
Main Methods:
- Planned balance attitude trajectories using high-order polynomial interpolation with attitude fluctuation counteraction.
- Generated leg trajectories based on planned attitude trajectories, considering terrain and swing leg path.
- Automatically generated support leg trajectories to meet balance attitude demands.
Main Results:
- Experimental validation on diverse terrains demonstrated the method's effectiveness.
- The proposed method simplified control system design compared to existing controllers.
- Significant improvement in the walking balance of the large-size hexapod robot was observed.
Conclusions:
- The attitude trajectory optimization method effectively enhances hexapod robot walking balance.
- The approach offers a simplified yet powerful solution for balance control in complex environments.
- This method improves environmental adaptability and control system efficiency for legged robots.
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