TY - GEN
T1 - Advancing Locomotion Control of a Quadruped Robot
T2 - 10th International Conference on Automation, Robotics, and Applications, ICARA 2024
AU - Du, Yixiong
AU - Liu, Zhuang
AU - Zhang, Xuping
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In order to achieve effective locomotion in complex terrain, it is crucial to implement a robust dynamics control scheme for the quadruped robot. This paper proposes a novel approach to locomotion control, utilizing both model predictive control (MPC) and sliding mode control (SMC). The proposed control scheme decomposes the whole control problem into body level and leg level. Firstly, the dynamics of the body are simplified and summarized into quadprog problem (QP), and the MPC-based controller is designed to solve the problem which is constrained by the range of ground reaction forces (GRFs) and the friction cone. Secondly, the neural network-based adaptive faster fixed-time nonsingular terminal sliding mode control (NTSMC) is utilized for the leg control. Thirdly, the proposed control scheme is verified of a trotting gait with the speed of 0.5 m/s and the simulation results indicate that the swing leg control has a tracking error below 0.01 m, and the body orientation errors are below 0.005 rad for roll, pitch, and yaw. Lastly, the proposed control scheme is validated with a digital twin in Webots.
AB - In order to achieve effective locomotion in complex terrain, it is crucial to implement a robust dynamics control scheme for the quadruped robot. This paper proposes a novel approach to locomotion control, utilizing both model predictive control (MPC) and sliding mode control (SMC). The proposed control scheme decomposes the whole control problem into body level and leg level. Firstly, the dynamics of the body are simplified and summarized into quadprog problem (QP), and the MPC-based controller is designed to solve the problem which is constrained by the range of ground reaction forces (GRFs) and the friction cone. Secondly, the neural network-based adaptive faster fixed-time nonsingular terminal sliding mode control (NTSMC) is utilized for the leg control. Thirdly, the proposed control scheme is verified of a trotting gait with the speed of 0.5 m/s and the simulation results indicate that the swing leg control has a tracking error below 0.01 m, and the body orientation errors are below 0.005 rad for roll, pitch, and yaw. Lastly, the proposed control scheme is validated with a digital twin in Webots.
KW - Adaptive neural network
KW - Digital twin
KW - Model predictive control
KW - Quadruped robot
KW - Sliding mode control
UR - http://www.scopus.com/inward/record.url?scp=85197361031&partnerID=8YFLogxK
U2 - 10.1109/ICARA60736.2024.10553027
DO - 10.1109/ICARA60736.2024.10553027
M3 - Article in proceedings
AN - SCOPUS:85197361031
T3 - International Conference on Automation, Robotics, and Applications, ICARA 2024 - Proceedings
SP - 144
EP - 149
BT - 2024 10th International Conference on Automation, Robotics, and Applications, ICARA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 22 February 2024 through 24 February 2024
ER -