Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm

Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm

This work addresses the multitask-based trajectory-planning problem (MTTP) for space robotics, which is an emerging application of successively executing tasks in assembly of the International Space Station. The MTTP is transformed into a parameter-optimization problem, where piecewise continuous-si...

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Main Authors: Suping Zhao, Zhanxia Zhu, Jianjun Luo
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Applied Sciences
Subjects:
space robotics
redundant
free-floating base
multiple tasks
trajectory planning
genetic algorithm
Online Access:https://www.mdpi.com/2076-3417/9/11/2226
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spelling doaj-7eff2dbce8ac41a491a9aa369141893b2020-11-25T01:59:00ZengMDPI AGApplied Sciences2076-34172019-05-01911222610.3390/app9112226app9112226Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic AlgorithmSuping Zhao0Zhanxia Zhu1Jianjun Luo2National Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi’an 710072, ChinaNational Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi’an 710072, ChinaNational Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi’an 710072, ChinaThis work addresses the multitask-based trajectory-planning problem (MTTP) for space robotics, which is an emerging application of successively executing tasks in assembly of the International Space Station. The MTTP is transformed into a parameter-optimization problem, where piecewise continuous-sine functions are employed to depict the joint trajectories. An improved genetic algorithm (IGA) is developed to optimize the unknown parameters. In the IGA, each chromosome consists of three parts, namely the waypoint sequence, the sequence of the joint configurations, and a special value for the depiction of the joint trajectories. Numerical simulations, including comparisons with two other approaches, are developed to test IGA validity.https://www.mdpi.com/2076-3417/9/11/2226space roboticsredundantfree-floating basemultiple taskstrajectory planninggenetic algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Suping Zhao
Zhanxia Zhu
Jianjun Luo
spellingShingle Suping Zhao
Zhanxia Zhu
Jianjun Luo
Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm
Applied Sciences
space robotics
redundant
free-floating base
multiple tasks
trajectory planning
genetic algorithm
author_facet Suping Zhao
Zhanxia Zhu
Jianjun Luo
author_sort Suping Zhao
title Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm
title_short Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm
title_full Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm
title_fullStr Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm
title_full_unstemmed Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm
title_sort multitask-based trajectory planning for redundant space robotics using improved genetic algorithm
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2019-05-01
description This work addresses the multitask-based trajectory-planning problem (MTTP) for space robotics, which is an emerging application of successively executing tasks in assembly of the International Space Station. The MTTP is transformed into a parameter-optimization problem, where piecewise continuous-sine functions are employed to depict the joint trajectories. An improved genetic algorithm (IGA) is developed to optimize the unknown parameters. In the IGA, each chromosome consists of three parts, namely the waypoint sequence, the sequence of the joint configurations, and a special value for the depiction of the joint trajectories. Numerical simulations, including comparisons with two other approaches, are developed to test IGA validity.
topic space robotics
redundant
free-floating base
multiple tasks
trajectory planning
genetic algorithm
url https://www.mdpi.com/2076-3417/9/11/2226
work_keys_str_mv AT supingzhao multitaskbasedtrajectoryplanningforredundantspaceroboticsusingimprovedgeneticalgorithm
AT zhanxiazhu multitaskbasedtrajectoryplanningforredundantspaceroboticsusingimprovedgeneticalgorithm
AT jianjunluo multitaskbasedtrajectoryplanningforredundantspaceroboticsusingimprovedgeneticalgorithm
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