Underwater Manipulator Trajectory Planning Based on Improved Particle Swarm Optimization Algorithm

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Názov: Underwater Manipulator Trajectory Planning Based on Improved Particle Swarm Optimization Algorithm
Autori: Huawei Jin, Guowen Yue
Zdroj: Journal of Field Robotics. 42:3986-4008
Informácie o vydavateľovi: Wiley, 2025.
Rok vydania: 2025
Popis: This study presents an innovative motion planning approach for underwater robotic arms, grounded in the multistrategy improved particle swarm optimization (PSO) (strategy adaptive particle swarm optimization [SAPSO]) algorithm. The SAPSO algorithm amalgamates the sine–cosine algorithm with the sparrow search algorithm, thereby enhancing the convergence efficiency and the capability to escape local optima inherent in PSO. Through the implementation of a 3–5–3 polynomial trajectory planning method, the proposed approach ensures a seamless transition from the initial to the target position while maintaining the continuity and fluidity of movement. Both simulation and underwater experimental analyses have validated the precision and efficacy of the SAPSO algorithm in collision detection, joint parameter optimization, and target capture operations. The outcomes underscore that the SAPSO algorithm considerably amplifies the speed and stability of trajectory planning and exhibits innovation and efficiency in the domain of underwater robotic arm motion planning.
Druh dokumentu: Article
Jazyk: English
ISSN: 1556-4967
1556-4959
DOI: 10.1002/rob.22603
Rights: Wiley Online Library User Agreement
Prístupové číslo: edsair.doi...........8aeed8e895d3f801574ac189bec7d05f
Databáza: OpenAIRE
Popis
Abstrakt:This study presents an innovative motion planning approach for underwater robotic arms, grounded in the multistrategy improved particle swarm optimization (PSO) (strategy adaptive particle swarm optimization [SAPSO]) algorithm. The SAPSO algorithm amalgamates the sine–cosine algorithm with the sparrow search algorithm, thereby enhancing the convergence efficiency and the capability to escape local optima inherent in PSO. Through the implementation of a 3–5–3 polynomial trajectory planning method, the proposed approach ensures a seamless transition from the initial to the target position while maintaining the continuity and fluidity of movement. Both simulation and underwater experimental analyses have validated the precision and efficacy of the SAPSO algorithm in collision detection, joint parameter optimization, and target capture operations. The outcomes underscore that the SAPSO algorithm considerably amplifies the speed and stability of trajectory planning and exhibits innovation and efficiency in the domain of underwater robotic arm motion planning.
ISSN:15564967
15564959
DOI:10.1002/rob.22603