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Improved dung beetle optimization algorithm based inverse kinematics solution for robotic arm

Published online by Cambridge University Press:  30 September 2025

Yunpeng Lv Open the ORCID record for Yunpeng Lv [Opens in a new window] ,
Hongbing Li ,
Siqi Zhu ,
Siyun Tan ,
Peng Yang  and
Chunzhe Zhao
Yunpeng Lv
Affiliation:
Chongqing Key Laboratory of Geological Environment Monitoring and Disaster Early Warning in the Three Gorges Reservoir Area, Chongqing Three Gorges University, Chongqing, China
Hongbing Li*
Affiliation:
Municipal Key Laboratory of Intelligent Information Processing and Control, Chongqing Three Gorges University, Chongqing, China Chongqing Engineering Research Center for Internet of Things and Intelligent Control Technology, Chongqing Three Gorges University, Chongqing, China
Siqi Zhu
Affiliation:
Municipal Key Laboratory of Intelligent Information Processing and Control, Chongqing Three Gorges University, Chongqing, China Chongqing Engineering Research Center for Internet of Things and Intelligent Control Technology, Chongqing Three Gorges University, Chongqing, China
Siyun Tan
Affiliation:
Municipal Key Laboratory of Intelligent Information Processing and Control, Chongqing Three Gorges University, Chongqing, China Chongqing Engineering Research Center for Internet of Things and Intelligent Control Technology, Chongqing Three Gorges University, Chongqing, China
Peng Yang
Affiliation:
Chongqing Key Laboratory of Geological Environment Monitoring and Disaster Early Warning in the Three Gorges Reservoir Area, Chongqing Three Gorges University, Chongqing, China
Chunzhe Zhao
Affiliation:
Municipal Key Laboratory of Intelligent Information Processing and Control, Chongqing Three Gorges University, Chongqing, China Chongqing Engineering Research Center for Internet of Things and Intelligent Control Technology, Chongqing Three Gorges University, Chongqing, China
*
Corresponding author: Hongbing Li; Email: cqlhb@qq.com
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Abstract

Aiming at the issues of more difficult to solve and lower precision of six-axis robotic arm in inverse kinematics (IK) solution, a multi-strategy improved dung beetle optimization algorithm (ECDBO) is proposed. It improves performance in four aspects: population initiation, global search capability, search direction perturbation and jumping out of local optima. Sobol sequence strategy was introduced to initialize the dung beetle population, resulting in a more even distribution of individual dung beetles and increasing the diversity of initial population. Boundary optimization strategy is adopted to balance the requirements on search capability at different times. This approach enhances global search capability at the beginning and local search capability at the end of an iteration. Propose hybrid directional perturbation strategy to change the search direction of rolling dung beetles and stealing dung beetles. It allows for more detailed exploration and improves convergence accuracy. The Levy flight strategy is incorporated to perturb current optimal solution, enhancing algorithm’s ability to jump out of the local optimum. In order to verify performance of ECDBO algorithm, CEC2017 function tests and robotic arm IK solving experiments were conducted and compared with other algorithms. ECDBO ranked first on 21 functions in the 30 dimensions tested in CEC2017 and on 27 functions in the 100 dimensions. ECDBO performs well in the IK solving experiments of two robotic arms with better accuracy than other algorithms. The experimental results show that the ECDBO algorithm significantly improves the convergence and accuracy, and also performs excellently on the IK solving problem.

Keywords

dung beetle optimization algorithmdirectional perturbationinverse kinematics solutionRobotic HandsSerial Manipulator Design and Kinematics

Information

Type
Research Article
Information
Robotica , First View , pp. 1 - 31
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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