Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm
In this study, by considering a space-based, n-joint manipulator system as research object, a kinematic and a dynamic model are constructed and the system’s nonholonomic property is discussed. In light of the nonholonomic property unique to space-based systems, a path planning method is introduced t...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2017/3207950 |
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| author | Zhengcang Chen Weijia Zhou |
| author_facet | Zhengcang Chen Weijia Zhou |
| author_sort | Zhengcang Chen |
| collection | DOAJ |
| description | In this study, by considering a space-based, n-joint manipulator system as research object, a kinematic and a dynamic model are constructed and the system’s nonholonomic property is discussed. In light of the nonholonomic property unique to space-based systems, a path planning method is introduced to ensure that when an end-effector moves to the desired position, a floating base achieves the expected pose. The trajectories of the joints are first parameterized using sinusoidal polynomial functions, and cost functions are defined by the pose deviation of the base and the positional error of the end-effector. At this stage, the path planning problem is converted into a target optimization problem, where the target is a function of the joints. We then adopt a quantum genetic algorithm (QGA) to solve this objective optimization problem to attain the optimized trajectories of the joints and then execute nonholonomic path planning. To test the proposed method, we carried out a simulation on a six-degree-of-freedom (DOF) space-based manipulator system (SBMS). The results showed that, compared to traditional genetic optimization algorithms, the QGA converges more rapidly and has a more accurate output. |
| format | Article |
| id | doaj-art-7819a119c52b44679026c7f0ed241d39 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-7819a119c52b44679026c7f0ed241d392025-02-03T05:46:35ZengWileyJournal of Robotics1687-96001687-96192017-01-01201710.1155/2017/32079503207950Path Planning for a Space-Based Manipulator System Based on Quantum Genetic AlgorithmZhengcang Chen0Weijia Zhou1State Key Laboratory of Robotics, Shenyang Institute of Automation, The Chinese Academy of Sciences (CAS), Shenyang 110016, ChinaUniversity of Chinese Academy of Science, Beijing, ChinaIn this study, by considering a space-based, n-joint manipulator system as research object, a kinematic and a dynamic model are constructed and the system’s nonholonomic property is discussed. In light of the nonholonomic property unique to space-based systems, a path planning method is introduced to ensure that when an end-effector moves to the desired position, a floating base achieves the expected pose. The trajectories of the joints are first parameterized using sinusoidal polynomial functions, and cost functions are defined by the pose deviation of the base and the positional error of the end-effector. At this stage, the path planning problem is converted into a target optimization problem, where the target is a function of the joints. We then adopt a quantum genetic algorithm (QGA) to solve this objective optimization problem to attain the optimized trajectories of the joints and then execute nonholonomic path planning. To test the proposed method, we carried out a simulation on a six-degree-of-freedom (DOF) space-based manipulator system (SBMS). The results showed that, compared to traditional genetic optimization algorithms, the QGA converges more rapidly and has a more accurate output.http://dx.doi.org/10.1155/2017/3207950 |
| spellingShingle | Zhengcang Chen Weijia Zhou Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm Journal of Robotics |
| title | Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm |
| title_full | Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm |
| title_fullStr | Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm |
| title_full_unstemmed | Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm |
| title_short | Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm |
| title_sort | path planning for a space based manipulator system based on quantum genetic algorithm |
| url | http://dx.doi.org/10.1155/2017/3207950 |
| work_keys_str_mv | AT zhengcangchen pathplanningforaspacebasedmanipulatorsystembasedonquantumgeneticalgorithm AT weijiazhou pathplanningforaspacebasedmanipulatorsystembasedonquantumgeneticalgorithm |