Research on Motion Control of Wheel-Legged Robot Based on ASMC and LQR

Wheel-legged robots combine the high-speed movement of wheeled robots with the superior obstacle-navigation abilities of legged robots. To enhance the robot's resilience against disturbances and improve its ability to overcome obstacles, we developed a control scheme that decouples the control into two parts: posture control and balance control. First, the robot's dynamics were modeled using the Euler-Lagrange method. To manage external disturbances, an Adaptive Sliding Mode Controller (ASMC) was designed to handle posture control. For balance control, a Linear Quadratic Regulator (LQR) was implemented to solve the Riccati equation in real-time, generating the necessary control torques to stabilize the robot. By combining these two control strategies, we present a framework that significantly improves the robot's mobility. Furthermore, tests conducted on a physical prototype demonstrated the effectiveness of the algorithm and the robot's disturbance rejection capability. The results confirm that the control scheme, which integrates ASMC and LQR, allows the wheel-legged robot to execute complex maneuvers and traverse uneven terrain with ease.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/iccsse63803.2024.10823686
Citations
1
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.18
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article

Research on Motion Control of Wheel-Legged Robot Based on ASMC and LQR

Yong Ding, Wang Yong, Ke Wu, Yi Wang
1 citations
Soft Robotics and Applications
0.18
article

Research on Motion Control of Wheel-Legged Robot Based on ASMC and LQR

Yong Ding, Wang Yong, Ke Wu, Yi Wang
article en
1 citations

Abstract

Wheel-legged robots combine the high-speed movement of wheeled robots with the superior obstacle-navigation abilities of legged robots. To enhance the robot's resilience against disturbances and improve its ability to overcome obstacles, we developed a control scheme that decouples the control into two parts: posture control and balance control. First, the robot's dynamics were modeled using the Euler-Lagrange method. To manage external disturbances, an Adaptive Sliding Mode Controller (ASMC) was designed to handle posture control. For balance control, a Linear Quadratic Regulator (LQR) was implemented to solve the Riccati equation in real-time, generating the necessary control torques to stabilize the robot. By combining these two control strategies, we present a framework that significantly improves the robot's mobility. Furthermore, tests conducted on a physical prototype demonstrated the effectiveness of the algorithm and the robot's disturbance rejection capability. The results confirm that the control scheme, which integrates ASMC and LQR, allows the wheel-legged robot to execute complex maneuvers and traverse uneven terrain with ease.

University of Science and Technology of China (CN)
Affordable and clean energy
Openalex Percentile: Top 49%
Soft Robotics and Applications
0.18
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Research on Motion Control of Wheel-Legged Robot Based on ASMC and LQR — Yong Ding, Wang Yong, et al. · (2024) | TGRS Research Map | TGRS