Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/82223
Title: | A new trajectory-planning beetle swarm optimization algorithm for trajectory planning of robot manipulators | Authors: | Wang, L Wu, Q Lin, F Li, S Chen, DC |
Issue Date: | 2019 | Source: | IEEE access, 24 Oct. 2019, v. 7, p. 154331-154345 | Abstract: | Based on a heuristic optimization algorithm, this paper proposes a new algorithm named trajectory-planning beetle swarm optimization (TPBSO) algorithm for solving trajectory planning of robots, especially robot manipulators. Firstly, two specific manipulator trajectory planning problems are presented as the practical application of the algorithm, which are point-to-point planning and fixed-geometric-path planning. Then, in order to verify the effectiveness of the algorithm, this paper develops a control model and conducts numerical experiments on two planning tasks. Moreover, it compares with existing algorithms to show the superiority of our proposed algorithm. Finally, the results of numerical comparisons show that algorithm has a relatively faster computational speed and better control performance without increasing computational complexity. | Keywords: | Beetle swarm optimization Robot manipulators Trajectory planning Optimization algorithms Control systems |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE access | EISSN: | 2169-3536 | DOI: | 10.1109/ACCESS.2019.2949271 | Rights: | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ The following publication L. Wang, Q. Wu, F. Lin, S. Li and D. Chen, "A New Trajectory-Planning Beetle Swarm Optimization Algorithm for Trajectory Planning of Robot Manipulators," in IEEE Access, vol. 7, pp. 154331-154345, 2019 is available at https://dx.doi.org/10.1109/ACCESS.2019.2949271 |
Appears in Collections: | Journal/Magazine Article |
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Wang_Trajectory-Planning_Beetle_Swarm.pdf | 1.62 MB | Adobe PDF | View/Open |
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