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

1,2, 1,2,* and 1,2
1
National Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi’an 710072, China
2
School of Astronautics, Northwestern Polytechnical University, Xi’an 710072, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(11), 2226; https://doi.org/10.3390/app9112226
Received: 29 April 2019 / Revised: 19 May 2019 / Accepted: 20 May 2019 / Published: 30 May 2019
(This article belongs to the Special Issue Mobile Robots Navigation)
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Abstract

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. View Full-Text
Keywords: space robotics; redundant; free-floating base; multiple tasks; trajectory planning; genetic algorithm space robotics; redundant; free-floating base; multiple tasks; trajectory planning; genetic algorithm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Zhao, S.; Zhu, Z.; Luo, J. Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm. Appl. Sci. 2019, 9, 2226.

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