Robot Time Optimal Trajectory Planning Based on Improved Simplified Particle Swarm Optimization Algorithm

In order to tackle the robot trajectory planning problem with the short running time as the optimization goal, a time-optimal trajectory planning algorithm was presented based on improved simplified particle swarm optimization (ISPSO). The robot’s trajectory was constructed by 3-5-3 polyn...

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Bibliographic Details
Main Authors: Hu, X. (Author), Liu, J. (Author), Sun, Q. (Author), Wu, H. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Subjects:
PSO
Online Access:View Fulltext in Publisher
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001 10.1109-ACCESS.2023.3272835
008 230529s2023 CNT 000 0 und d
020 |a 21693536 (ISSN) 
245 1 0 |a Robot Time Optimal Trajectory Planning Based on Improved Simplified Particle Swarm Optimization Algorithm 
260 0 |b Institute of Electrical and Electronics Engineers Inc.  |c 2023 
300 |a 1 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1109/ACCESS.2023.3272835 
856 |z View in Scopus  |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159687689&doi=10.1109%2fACCESS.2023.3272835&partnerID=40&md5=2cf6d177f06d60c3cd8f517c2008928e 
520 3 |a In order to tackle the robot trajectory planning problem with the short running time as the optimization goal, a time-optimal trajectory planning algorithm was presented based on improved simplified particle swarm optimization (ISPSO). The robot’s trajectory was constructed by 3-5-3 polynomial interpolation in the joint space of the robot. Under the condition of satisfying the velocity constraint, the objective function was constructed by the sum of the time intervals between each node. ISPSO was used to optimize the objective function. The algorithm was improved by optimizing the inertia weight updating method and introducing a golden sine segmentation algorithm as an optimization operator. Compared with other particle swarm optimization algorithms, ISPSO had higher search velocity and accuracy. The effectiveness of the proposed algorithm was demonstrated through simulations using the PUMA 560 industrial robot, which resulted in a 19% reduction in time compared to the simplified particle swarm algorithm. The simulation results show that ISPSO achieved time optimization under the condition of velocity constraint, which proved its superiority in trajectory planning. Author 
650 0 4 |a Interpolation 
650 0 4 |a Optimization 
650 0 4 |a Particle swarm optimization 
650 0 4 |a polynomial interpolation 
650 0 4 |a PSO 
650 0 4 |a Robots 
650 0 4 |a Service robots 
650 0 4 |a time-optimal 
650 0 4 |a Trajectory 
650 0 4 |a Trajectory planning 
700 1 0 |a Hu, X.  |e author 
700 1 0 |a Liu, J.  |e author 
700 1 0 |a Sun, Q.  |e author 
700 1 0 |a Wu, H.  |e author 
773 |t IEEE Access