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3D-SLIP model based dynamic stability strategy for legged robots with impact disturbance rejection
Bin Han1, Haoyuan Yi1, Zhenyu Xu1
1State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China.
Scientific Reports
|April 8, 2022
Summary
This study introduces a 3D-HFC control strategy for legged robots to maintain stability during lateral impacts. The method uses touchdown angle, body attitude, and energy compensation to reject disturbances in 3D locomotion.
Area of Science:
- Robotics
- Biomechanics
- Control Systems
Background:
- The 2D spring-loaded inverted pendulum model effectively describes running but struggles with 3D lateral disturbances.
- Increased degrees of freedom in 3D locomotion lead to higher computational complexity and control challenges for legged robots.
Purpose of the Study:
- To develop a robust control strategy for legged locomotion that can effectively reject lateral impact disturbances.
- To enhance the stability and adaptability of legged robots in dynamic, three-dimensional environments.
Main Methods:
- A novel 3D-HFC control strategy was developed, building upon the classical Raibert controller.
- The strategy integrates touchdown angle control, body attitude angle control, and energy compensation modules.
- Real-time energy loss measurement and prediction were incorporated to manage step-to-step dynamics.
Main Results:
- The 3D-HFC strategy demonstrated efficiency in simulations using a 3D-SLIP model and a quadruped robot under various impact forces.
- Experimental validation on a quadruped bionic prototype (MBBOT) confirmed the strategy's effectiveness in rejecting lateral impact disturbances.
- Both simulation and real-world experiments showed successful disturbance rejection capabilities.
Conclusions:
- The proposed 3D-HFC control strategy enables legged robots to maintain stability and reject lateral impact disturbances in 3D locomotion.
- This approach enhances the robustness of legged robots, making them more adaptable to complex and unpredictable environments.

