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Trajectory Planning of Robotic Arm Based on Particle Swarm Optimization Algorithm

Nengkai Wu, Dongyao Jia, Ziqi Li, Zihao He

Year
2024
Citations
21
Access
Open access

Abstract

Achieving vibration-free smooth motion of industrial robotic arms in a short period is an important research topic. Existing path planning algorithms often sacrifice smoothness in pursuit of efficient motion. A robotic trajectory planning particle swarm optimization algorithm (RTPPSO) is introduced for optimizing joint angles or paths of mechanical arm movements. The RTPPSO algorithm is enhanced through the introduction of adaptive weight strategies and random perturbation terms. Subsequently, the RTPPSO algorithm is utilized to plan selected parameters of an S-shaped velocity profile, iterating to obtain the optimal solution. Experimental results demonstrate that this velocity planning algorithm significantly improves the acceleration of the robotic arm, surpassing traditional trial-and-error velocity planning methods.

Keywords

Particle swarm optimizationComputer scienceMulti-swarm optimizationMotion planningAlgorithmMathematical optimizationArtificial intelligenceComputer visionMathematicsRobot

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