Robotic arm path planning based on the improved dung beetle optimization algorithm
XUAN Yitong
LI Lijun
CHEN Haifei
Abstract：[Objective]A path planning algorithm based on an improved dung beetle optimization algorithm was proposed to address the challenges in complex scenarios where traditional algorithms for robotic arm path planning often suffer from low efficiency and susceptibility to local optima.[Methods]Firstly,the robotic arm and obstacles were modeled using the bounding box method.An optimization function was established based on path length,joint motion smoothness,and collision avoidance.Secondly,the algorithm incorporated Logistic mapping for population initialization to enhance diversity and improved the heuris-tic mechanism to accelerate convergence.It introduced an adaptive polynomial mutation to escape local optima.Thirdly,the comparative simulations were conducted using basic dung beetle algorithm,jellyfish algorithm,grey wolf algorithm,whale algo-rithm,and the improved dung beetle algorithm in Matlab software.Finally,the real-world testing was conducted.[Results]The results indicate that the proposed algorithm is less prone to getting trapped in local optima,achieves faster convergence,shorter computation time,and higher optimization accuracy when solving robotic arm path planning problems.The algorithm's reliabili-ty is validated through the real-world testing.
Keywords：Six-axis robotic armImproved dung beetle algorithmChaotic mappingPolynomial mutation
Publication Date：2025-02-14
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：9( 70-78 )