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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Main Authors: Wenfu Xu, Cheng Li, Bin Liang, Yu Liu, Yangsheng Xu
Format: Article
Language:English
Published: SAGE Publishing 2008-09-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.5772/5605
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spelling 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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