Time optimal trajectory planning of robotic arm based on improved tuna swarm algorithm

被引：2
作者：
Wu, Jichun [1 ]
Zhang, Zhaiwu [1 ]
Yang, Yongda [1 ]
Zhang, Ping [1 ]
Fan, Dapeng [2 ]
机构：
[1] School of Mechanical Engineering and Mechanics, Xiangtan University, Xiangtan
[2] Engineering Intelligent Academy of Sciences, National University of Defense Technology, Changsha
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2024年 / 30卷 / 12期
关键词：
adaptive threshold; chaotic population initialization; improved tuna swarm optimization algorithm; Levy flight; trajectory planning;
D O I：
10.13196/j.cims.2023.0528
中图分类号：
学科分类号：
摘要：
To enable the robotic arm to complete tasks quickly while satisfying kinematic constraints during its movement, an optimal time trajectory planning method for robotic arm based on improved Tuna Swarm Optimization(TSO) algorithm was proposed, which was optimized on the standard TSO algorithm and improved by employing the tent chaotic population initialization and Levy flight. An adaptive threshold was introduced to improve the performance of the algorithm. A mathematical model for time optimization objectives was established by taking 6-degree-of-freedom serial manipulator as the research subject, and a 3-5-3 blended polynomial interpolation function was employed as the foundation for trajectory planning. Experimental results showed that the improved TSO algorithm had higher optimization accuracy and a more robust ability to escape local optimal solutions than the original algorithms. The optimized robotic arm′s displacement, velocity and acceleration curves were smooth and free from abrupt changes, which indicated that the improved TSO algorithm could effectively achieve optimal time trajectory planning for the robotic arm. © 2024 CIMS. All rights reserved.
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页码：4292 / 4301
页数：9
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