A CPG-based gait planning and motion performance analysis for quadruped robot
ISSN: 0143-991x
Article publication date: 21 January 2022
Issue publication date: 1 June 2022
Abstract
Purpose
To achieve stable gait planning and enhance the motion performance of quadruped robot, this paper aims to propose a motion control strategy based on central pattern generator (CPG) and back-propagation neural network (BPNN).
Design/methodology/approach
First, the Kuramoto phase oscillator is used to construct the CPG network model, and a piecewise continuous phase difference matrix is designed to optimize the duty cycle of walk gait, so as to realize the gait planning and smooth switching. Second, the mapper between CPG output and joint drive is established based on BP neural network, so that the quadruped robot based on CPG control has better foot trajectory to enhance the motion performance. Finally, to obtain better mapping effect, an evaluation function is resigned to evaluate the proximity between the actual foot trajectory and the ideal foot trajectory. Genetic algorithm and particle swarm optimization are used to optimize the initial weights and thresholds of BPNN to obtain more accurate foot trajectory.
Findings
The method provides a solution for the smooth gait switching and foot trajectory of the robot. The quintic polynomial trajectory is selected to testify the validity and practicability of the method through simulation and prototype experiment.
Originality/value
The paper solved the incorrect duty cycle under the walk gait of CPG network constructed by Kuramoto phase oscillator, and made the robot have a better foot trajectory by mapper to enhance its motion performance.
Keywords
Acknowledgements
Funding: Candidate Talents Training Fund of Yunnan Province (KKSY201701001). National Natural Science Foundation of China (51965029) (52065035).
Citation
Wei, S., Wu, H., Liu, L., Zhang, Y., Chen, J. and Li, Q. (2022), "A CPG-based gait planning and motion performance analysis for quadruped robot", Industrial Robot, Vol. 49 No. 4, pp. 779-797. https://doi.org/10.1108/IR-08-2021-0181
Publisher
:Emerald Publishing Limited
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