Issue |
Int. J. Metrol. Qual. Eng.
Volume 10, 2019
|
|
---|---|---|
Article Number | 11 | |
Number of page(s) | 6 | |
DOI | https://doi.org/10.1051/ijmqe/2019011 | |
Published online | 25 September 2019 |
Research Article
Motion planning optimization of trajectory path of space manipulators
College of Architecture and Geomatics Engineering, Shanxi Datong University, Datong, Shanxi 037009, PR China
* Corresponding author: qiaodong_dq@163.com
Received:
11
July
2019
Accepted:
30
August
2019
With the development of the aerospace industry, the work carried out inside and outside the weightless space station is becoming more and more complicated. In order to ensure the safety of astronauts, space manipulators are used for operation, but it will disturb the space station that is a base during work. In order to solve the above problems, in this paper, the planning method of the motion trajectory of manipulators, the motion model of manipulators and the particle swarm optimization (PSO) algorithm used for optimizing the trajectory are briefly introduced, the multi-population co-evolution method is used to improve the PSO algorithm, and the above two algorithms are used to optimize the motion trajectory of the floating pedestal space manipulator with three free degrees of rotation in the same plane by the matrix laboratory (MATLAB) software. It is compared with genetic algorithm. The results show that the improved PSO algorithm can converge to a better global optimal fitness with fewer iterations compared with the traditional PSO algorithm and genetic algorithm. The obtained motion trajectory optimized by the improved PSO algorithm has less disturbances to the pedestal posture, and less time is required to achieve the target motion; moreover the changes of mechanical arm joint are more stable during the motion.
Key words: Space manipulator / path optimization / particle swarm optimization algorithm / co-evolution
© D. Qiao, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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