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Motion control of legged robots based on gradient central pattern generators

Published online by Cambridge University Press:  18 October 2024

Yihui Zhang ,
Wenshuo Liu  and
Ning Tan Open the ORCID record for Ning Tan [Opens in a new window]
Yihui Zhang
Affiliation:
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
Wenshuo Liu
Affiliation:
Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, Sun Yat-sen University, Guangzhou, China
Ning Tan*
Affiliation:
Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, Sun Yat-sen University, Guangzhou, China
*
Corresponding author: Ning Tan; Email: tann5@mail.sysu.edu.cn
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Abstract

The design of motion control systems for legged robots has always been a challenge. This article first proposes a motion control method for legged robots based on the gradient central pattern generator (GD-CPG). The periodic signals output from the GD-CPG neural network are used as the drive signals of each thigh joint of the legged robots, which are then converted into the driving signal of the knee and ankle joints by the thigh–knee mapping function and the knee–ankle mapping function. The proposed control algorithm is adapted to quadruped and hexapod robots. To improve the ability of legged robots to cope with complex terrains, this article further proposes the responsive gradient-CPG motion control method for legged robots. From the perspective of bionics, a biological vestibular sensory feedback mechanism is established in the control system. The mechanism adjusts the robot’s motion state in real time through the attitude angle of the body measured during the robot’s motion, to keep the robot’s body stable when it moves in rugged terrains. Compared with the traditional feedback model that only balances the body pitch, this article also adds the balancing functions of body roll and yaw to balance the legged robot’s motion from more dimensions and improve the linear motion capability. This article also introduces a differential evolutionary algorithm and designs a fitness function to adaptively optimize vestibular sensory feedback parameters. The validity, robustness, and transferability of the method are verified through simulations and physical experiments.

Keywords

Central pattern generatorlegged robotlocomotion controlvestibular sensory feedbackdifferential evolutionary

Information

Type
Research Article
Information
Robotica , Volume 42 , Issue 9 , September 2024 , pp. 3102 - 3131
Copyright
© The Author(s), 2024. Published by Cambridge University Press

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