The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization
The Cartesian path planning of free-floating space robot is much more complex than that of fixed-based manipulators, since the end-effector pose (position and orientation) is path dependent, and the position-level kinematic equations can not be used to determine the joint angles. In this paper, a me...
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doaj-8626365ae85d4bdd991829d4a6930e2c2020-11-25T03:45:17ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142008-09-01510.5772/560510.5772_5605The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm OptimizationWenfu Xu0Cheng Li1Bin Liang2Yu Liu3Yangsheng Xu4 The Institute of Space Intelligent System Harbin Institute of Technology, Harbin, P.R. China The Institute of Space Intelligent System Harbin Institute of Technology, Harbin, P.R. China The Institute of Space Intelligent System Harbin Institute of Technology, Harbin, P.R. China The Institute of Space Intelligent System Harbin Institute of Technology, Harbin, P.R. China Dept. of Automation and Computer-Aided Engineering The Chinese University of Hong Kong, Hong Kong, P.R.ChinaThe Cartesian path planning of free-floating space robot is much more complex than that of fixed-based manipulators, since the end-effector pose (position and orientation) is path dependent, and the position-level kinematic equations can not be used to determine the joint angles. In this paper, a method based on particle swarm optimization (PSO) is proposed to solve this problem. Firstly, we parameterize the joint trajectory using polynomial functions, and then normalize the parameterized trajectory. Secondly, the Cartesian path planning is transformed to an optimization problem by integrating the differential kinematic equations. The object function is defined according to the accuracy requirement, and it is the function of the parameters to be defined. Finally, we use the Particle Swarm Optimization (PSO) algorithm to search the unknown parameters. The approach has the following traits: 1) The limits on joint angles, rates and accelerations are included in the planning algorithm; 2) There exist not any kinematic and dynamic singularities, since only the direct kinematic equations are used; 3) The attitude singularities do not exist, for the orientation is represented by quaternion; 4) The optimization algorithm is not affected by the initial parameters. Simulation results verify the proposed method.https://doi.org/10.5772/5605 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wenfu Xu Cheng Li Bin Liang Yu Liu Yangsheng Xu |
spellingShingle |
Wenfu Xu Cheng Li Bin Liang Yu Liu Yangsheng Xu The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization International Journal of Advanced Robotic Systems |
author_facet |
Wenfu Xu Cheng Li Bin Liang Yu Liu Yangsheng Xu |
author_sort |
Wenfu Xu |
title |
The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization |
title_short |
The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization |
title_full |
The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization |
title_fullStr |
The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization |
title_full_unstemmed |
The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization |
title_sort |
cartesian path planning of free-floating space robot using particle swarm optimization |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2008-09-01 |
description |
The Cartesian path planning of free-floating space robot is much more complex than that of fixed-based manipulators, since the end-effector pose (position and orientation) is path dependent, and the position-level kinematic equations can not be used to determine the joint angles. In this paper, a method based on particle swarm optimization (PSO) is proposed to solve this problem. Firstly, we parameterize the joint trajectory using polynomial functions, and then normalize the parameterized trajectory. Secondly, the Cartesian path planning is transformed to an optimization problem by integrating the differential kinematic equations. The object function is defined according to the accuracy requirement, and it is the function of the parameters to be defined. Finally, we use the Particle Swarm Optimization (PSO) algorithm to search the unknown parameters. The approach has the following traits: 1) The limits on joint angles, rates and accelerations are included in the planning algorithm; 2) There exist not any kinematic and dynamic singularities, since only the direct kinematic equations are used; 3) The attitude singularities do not exist, for the orientation is represented by quaternion; 4) The optimization algorithm is not affected by the initial parameters. Simulation results verify the proposed method. |
url |
https://doi.org/10.5772/5605 |
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