Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics
Motion planning is one of the most important technologies for free-floating space robots (FFSRs) to increase operation safety and autonomy in orbit. As a nonholonomic system, a first-order differential relationship exists between the joint angle and the base attitude of the space robot, which makes...
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| Formato: | Artigo |
| Idioma: | English |
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MDPI AG
2020-12-01
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| Series: | Applied Sciences |
| Subjects: | |
| Acceso en liña: | https://www.mdpi.com/2076-3417/10/24/9137 |
| _version_ | 1827699566566178816 |
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| author | Hongwen Zhang Zhanxia Zhu |
| author_facet | Hongwen Zhang Zhanxia Zhu |
| author_sort | Hongwen Zhang |
| collection | DOAJ |
| description | Motion planning is one of the most important technologies for free-floating space robots (FFSRs) to increase operation safety and autonomy in orbit. As a nonholonomic system, a first-order differential relationship exists between the joint angle and the base attitude of the space robot, which makes it pretty challenging to implement the relevant motion planning. Meanwhile, the existing planning framework must solve inverse kinematics for goal configuration and has the limitation that the goal configuration and the initial configuration may not be in the same connected domain. Thus, faced with these questions, this paper investigates a novel motion planning algorithm based on rapidly-exploring random trees (RRTs) for an FFSR from an initial configuration to a goal end-effector (EE) pose. In a motion planning algorithm designed to deal with differential constraints and restrict base attitude disturbance, two control-based local planners are proposed, respectively, for random configuration guiding growth and goal EE pose-guiding growth of the tree. The former can ensure the effective exploration of the configuration space, and the latter can reduce the possibility of occurrence of singularity while ensuring the fast convergence of the algorithm and no violation of the attitude constraints. Compared with the existing works, it does not require the inverse kinematics to be solved while the planning task is completed and the attitude constraint is preserved. The simulation results verify the effectiveness of the algorithm. |
| first_indexed | 2024-03-10T13:53:36Z |
| format | Article |
| id | doaj.art-98ce4cb6167547cf8046a9acbb881dbf |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T13:53:36Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-98ce4cb6167547cf8046a9acbb881dbf2023-11-21T01:54:32ZengMDPI AGApplied Sciences2076-34172020-12-011024913710.3390/app10249137Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse KinematicsHongwen Zhang0Zhanxia Zhu1National Key Laboratory of Aerospace Flight Dynamics, School of Astronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaNational Key Laboratory of Aerospace Flight Dynamics, School of Astronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaMotion planning is one of the most important technologies for free-floating space robots (FFSRs) to increase operation safety and autonomy in orbit. As a nonholonomic system, a first-order differential relationship exists between the joint angle and the base attitude of the space robot, which makes it pretty challenging to implement the relevant motion planning. Meanwhile, the existing planning framework must solve inverse kinematics for goal configuration and has the limitation that the goal configuration and the initial configuration may not be in the same connected domain. Thus, faced with these questions, this paper investigates a novel motion planning algorithm based on rapidly-exploring random trees (RRTs) for an FFSR from an initial configuration to a goal end-effector (EE) pose. In a motion planning algorithm designed to deal with differential constraints and restrict base attitude disturbance, two control-based local planners are proposed, respectively, for random configuration guiding growth and goal EE pose-guiding growth of the tree. The former can ensure the effective exploration of the configuration space, and the latter can reduce the possibility of occurrence of singularity while ensuring the fast convergence of the algorithm and no violation of the attitude constraints. Compared with the existing works, it does not require the inverse kinematics to be solved while the planning task is completed and the attitude constraint is preserved. The simulation results verify the effectiveness of the algorithm.https://www.mdpi.com/2076-3417/10/24/9137free-floating space robotmotion planningsampling-based motion planningnonholonomic robot |
| spellingShingle | Hongwen Zhang Zhanxia Zhu Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics Applied Sciences free-floating space robot motion planning sampling-based motion planning nonholonomic robot |
| title | Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics |
| title_full | Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics |
| title_fullStr | Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics |
| title_full_unstemmed | Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics |
| title_short | Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics |
| title_sort | sampling based motion planning for free floating space robot without inverse kinematics |
| topic | free-floating space robot motion planning sampling-based motion planning nonholonomic robot |
| url | https://www.mdpi.com/2076-3417/10/24/9137 |
| work_keys_str_mv | AT hongwenzhang samplingbasedmotionplanningforfreefloatingspacerobotwithoutinversekinematics AT zhanxiazhu samplingbasedmotionplanningforfreefloatingspacerobotwithoutinversekinematics |