Improved Particle Swarm Optimization for Trajectory Planning in a Six-Degree-of-Freedom Robotic Arm

Aiming at the problem of the UR5 robot's unsmooth trajectory during operation, in order to improve the robot's motion accuracy and operation efficiency, this paper proposes a joint space trajectory planning method based on 3-5-3 piecewise polynomial interpolation, which can better meet the speed and acceleration constraints of the robot in different motion stages while ensuring the smoothness of the trajectory, thereby improving the operation stability of the robot. Under the conditions of satisfying the speed and acceleration constraints, the improved particle swarm optimization (PSO) algorithm with the introduction of compression factor and improved adaptive factor is used to optimize the interpolation time of the robot. Compared with the traditional PSO algorithm, the improved PSO algorithm is not easy to fall into the local optimum, making the trajectory planning more efficient. The experimental results show that the improved PSO algorithm not only significantly shortens the operation time of the robot, but also makes the trajectory smoother and the overall operation effect better.

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Publication Details

Published
2024-09-13
DOI
https://doi.org/10.1109/icacte62428.2024.10871589
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25
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article

Improved Particle Swarm Optimization for Trajectory Planning in a Six-Degree-of-Freedom Robotic Arm

Jianzhong Zhang, Pengju Wang
1 citations
Robotic Path Planning Algorithms
0.25
article

Improved Particle Swarm Optimization for Trajectory Planning in a Six-Degree-of-Freedom Robotic Arm

Jianzhong Zhang, Pengju Wang
article en
1 citations

Abstract

Aiming at the problem of the UR5 robot's unsmooth trajectory during operation, in order to improve the robot's motion accuracy and operation efficiency, this paper proposes a joint space trajectory planning method based on 3-5-3 piecewise polynomial interpolation, which can better meet the speed and acceleration constraints of the robot in different motion stages while ensuring the smoothness of the trajectory, thereby improving the operation stability of the robot. Under the conditions of satisfying the speed and acceleration constraints, the improved particle swarm optimization (PSO) algorithm with the introduction of compression factor and improved adaptive factor is used to optimize the interpolation time of the robot. Compared with the traditional PSO algorithm, the improved PSO algorithm is not easy to fall into the local optimum, making the trajectory planning more efficient. The experimental results show that the improved PSO algorithm not only significantly shortens the operation time of the robot, but also makes the trajectory smoother and the overall operation effect better.

Anhui Jianzhu University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 42%
Robotic Path Planning Algorithms
0.25
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