TRAJECTORY PLANNING OF REDUNDANT SPACE MANIPULATORS FOR MULTI-TASKS

Suping Zhao; Zhanxia Zhu; Chaobo Chen; Yushuang Du; Xiaohua Song; Kun Yan; Dacheng Jiang; Lin Li; An Liu

doi:10.2316/J.2023.206-0804

TRAJECTORY PLANNING OF REDUNDANT SPACE MANIPULATORS FOR MULTI-TASKS

Suping Zhao, Zhanxia Zhu, Chaobo Chen, Yushuang Du, Xiaohua Song, Kun Yan, Dacheng Jiang, Lin Li, An Liu

School of Astronautics

Xi'an Technological University

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

The trajectory planning is addressed for a redundant space manipulator. The end effector is constrained to visit a set of predefined task points with minimum energy cost. In addition, minimum manipulator manoeuvre time and minimal attitude disturbance on free-floating base spacecraft are considered. The trajectory planning problem is studied as an optimisation problem, including the sequential order of task points, the joint configurations corresponding to each task point, and a shared coefficient. An improved genetic algorithm (IGA) is proposed to optimise the aforementioned parameters. In IGA, each chromosome consists of three parts, namely, the tasks points, the joint configurations, and the shared coefficient. Numerical simulations and comparisons are carried out to verify the proposed method.

Original language	English
Pages (from-to)	344-351
Number of pages	8
Journal	International Journal of Robotics and Automation
Volume	38
Issue number	5
DOIs	https://doi.org/10.2316/J.2023.206-0804
State	Published - 2023

Keywords

improved genetic algorithm
multiple tasks
Redundant space manipulator
time-energy optimal
trajectory planning

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title = "TRAJECTORY PLANNING OF REDUNDANT SPACE MANIPULATORS FOR MULTI-TASKS",

abstract = "The trajectory planning is addressed for a redundant space manipulator. The end effector is constrained to visit a set of predefined task points with minimum energy cost. In addition, minimum manipulator manoeuvre time and minimal attitude disturbance on free-floating base spacecraft are considered. The trajectory planning problem is studied as an optimisation problem, including the sequential order of task points, the joint configurations corresponding to each task point, and a shared coefficient. An improved genetic algorithm (IGA) is proposed to optimise the aforementioned parameters. In IGA, each chromosome consists of three parts, namely, the tasks points, the joint configurations, and the shared coefficient. Numerical simulations and comparisons are carried out to verify the proposed method.",

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author = "Suping Zhao and Zhanxia Zhu and Chaobo Chen and Yushuang Du and Xiaohua Song and Kun Yan and Dacheng Jiang and Lin Li and An Liu",

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T1 - TRAJECTORY PLANNING OF REDUNDANT SPACE MANIPULATORS FOR MULTI-TASKS

AU - Zhao, Suping

AU - Zhu, Zhanxia

AU - Chen, Chaobo

AU - Du, Yushuang

AU - Song, Xiaohua

AU - Yan, Kun

AU - Jiang, Dacheng

AU - Li, Lin

AU - Liu, An

PY - 2023

Y1 - 2023

N2 - The trajectory planning is addressed for a redundant space manipulator. The end effector is constrained to visit a set of predefined task points with minimum energy cost. In addition, minimum manipulator manoeuvre time and minimal attitude disturbance on free-floating base spacecraft are considered. The trajectory planning problem is studied as an optimisation problem, including the sequential order of task points, the joint configurations corresponding to each task point, and a shared coefficient. An improved genetic algorithm (IGA) is proposed to optimise the aforementioned parameters. In IGA, each chromosome consists of three parts, namely, the tasks points, the joint configurations, and the shared coefficient. Numerical simulations and comparisons are carried out to verify the proposed method.

AB - The trajectory planning is addressed for a redundant space manipulator. The end effector is constrained to visit a set of predefined task points with minimum energy cost. In addition, minimum manipulator manoeuvre time and minimal attitude disturbance on free-floating base spacecraft are considered. The trajectory planning problem is studied as an optimisation problem, including the sequential order of task points, the joint configurations corresponding to each task point, and a shared coefficient. An improved genetic algorithm (IGA) is proposed to optimise the aforementioned parameters. In IGA, each chromosome consists of three parts, namely, the tasks points, the joint configurations, and the shared coefficient. Numerical simulations and comparisons are carried out to verify the proposed method.

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KW - Redundant space manipulator

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TRAJECTORY PLANNING OF REDUNDANT SPACE MANIPULATORS FOR MULTI-TASKS

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Keywords

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