A Hybrid Improved-Whale-Optimization–Simulated-Annealing Algorithm for Trajectory Planning of Quadruped Robots

Traditional trajectory-planning methods are unable to achieve time optimization, resulting in slow response times to unexpected situations. To address this issue and improve the smoothness of joint trajectories and the movement time of quadruped robots, we propose a trajectory-planning method based...

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Bibliographic Details
Published in:Electronics (Basel) Vol. 12; no. 7; p. 1564
Main Authors: Xu, Ruoyu, Zhao, Chunhui, Li, Jiaxing, Hu, Jinwen, Hou, Xiaolei
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.04.2023
Subjects:
Algorithms
Angular velocity
Control systems
Kinematics
Markov chains
Mathematical optimization
Optimization
Optimization algorithms
Planning
Robots
Simulated annealing
Simulated annealing (Mathematics)
Smoothness
Speed limits
Stochastic processes
Trajectory planning
Velocity
Whales & whaling
China
ISSN:2079-9292, 2079-9292
Online Access:Get full text
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Summary:Traditional trajectory-planning methods are unable to achieve time optimization, resulting in slow response times to unexpected situations. To address this issue and improve the smoothness of joint trajectories and the movement time of quadruped robots, we propose a trajectory-planning method based on time optimization. This approach improves the whale optimization algorithm with simulated annealing (IWOA-SA) together with adaptive weights to prevent the whale optimization algorithm (WOA) from falling into local optima and to balance its exploration and exploitation abilities. We also use Markov chains of stochastic process theory to analyze the global convergence of the proposed algorithm. The results show that our optimization algorithm has stronger optimization ability and stability when compared to six representative algorithms using six different test function suites in multiple dimensions. Additionally, the proposed optimization algorithm consistently constrains the angular velocity of each joint within the range of kinematic constraints and reduces joint running time by approximately 6.25%, which indicates the effectiveness of this algorithm.
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ISSN:2079-9292
2079-9292
DOI:10.3390/electronics12071564