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Underwater Manipulator Trajectory Planning Based on Improved Particle Swarm Optimization Algorithm

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Bibliographic Details
Title: Underwater Manipulator Trajectory Planning Based on Improved Particle Swarm Optimization Algorithm
Authors: Huawei Jin, Guowen Yue
Source: Journal of Field Robotics. 42:3986-4008
Publisher Information: Wiley, 2025.
Publication Year: 2025
Description: 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.
Document Type: Article
Language: English
ISSN: 1556-4967
1556-4959
DOI: 10.1002/rob.22603
Rights: Wiley Online Library User Agreement
Accession Number: edsair.doi...........8aeed8e895d3f801574ac189bec7d05f
Database: OpenAIRE
Description
Abstract: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