Robotic arm trajectory optimization based on multiverse algorithm
For inefficient trajectory planning of six-degree-of-freedom industrial manipulators, a trajectory planning algorithm based on an improved multiverse algorithm (IMVO) for time, energy, and impact optimization are proposed. The multi-universe algorithm has better robustness and convergence accuracy i...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2023-01-01
|
| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2023130?viewType=HTML |
| _version_ | 1811175523547611136 |
|---|---|
| author | Junjie Liu Hui Wang Xue Li Kai Chen Chaoyu Li |
| author_facet | Junjie Liu Hui Wang Xue Li Kai Chen Chaoyu Li |
| author_sort | Junjie Liu |
| collection | DOAJ |
| description | For inefficient trajectory planning of six-degree-of-freedom industrial manipulators, a trajectory planning algorithm based on an improved multiverse algorithm (IMVO) for time, energy, and impact optimization are proposed. The multi-universe algorithm has better robustness and convergence accuracy in solving single-objective constrained optimization problems than other algorithms. In contrast, it has the disadvantage of slow convergence and quickly falls into local optimum. This paper proposes a method to improve the wormhole probability curve, adaptive parameter adjustment, and population mutation fusion to improve the convergence speed and global search capability. In this paper, we modify MVO for multi-objective optimization to derive the Pareto solution set. We then construct the objective function by a weighted approach and optimize it using IMVO. The results show that the algorithm improves the timeliness of the six-degree-of-freedom manipulator trajectory operation within a specific constraint and improves the optimal time, energy consumption, and impact problems in the manipulator trajectory planning. |
| first_indexed | 2024-04-10T19:37:19Z |
| format | Article |
| id | doaj.art-13b6f4c78f7743b38d76ed0a17fb8df5 |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-04-10T19:37:19Z |
| publishDate | 2023-01-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-13b6f4c78f7743b38d76ed0a17fb8df52023-01-30T01:30:24ZengAIMS PressMathematical Biosciences and Engineering1551-00182023-01-012022776279210.3934/mbe.2023130Robotic arm trajectory optimization based on multiverse algorithmJunjie Liu 0Hui Wang1Xue Li2Kai Chen3Chaoyu Li 41. School of Mechanical and Electronic Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China1. School of Mechanical and Electronic Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China2. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China1. School of Mechanical and Electronic Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China1. School of Mechanical and Electronic Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaFor inefficient trajectory planning of six-degree-of-freedom industrial manipulators, a trajectory planning algorithm based on an improved multiverse algorithm (IMVO) for time, energy, and impact optimization are proposed. The multi-universe algorithm has better robustness and convergence accuracy in solving single-objective constrained optimization problems than other algorithms. In contrast, it has the disadvantage of slow convergence and quickly falls into local optimum. This paper proposes a method to improve the wormhole probability curve, adaptive parameter adjustment, and population mutation fusion to improve the convergence speed and global search capability. In this paper, we modify MVO for multi-objective optimization to derive the Pareto solution set. We then construct the objective function by a weighted approach and optimize it using IMVO. The results show that the algorithm improves the timeliness of the six-degree-of-freedom manipulator trajectory operation within a specific constraint and improves the optimal time, energy consumption, and impact problems in the manipulator trajectory planning.https://www.aimspress.com/article/doi/10.3934/mbe.2023130?viewType=HTMLtrajectory planningoptimization algorithmoptimal timeoptimal energy consumptionoptimal impact |
| spellingShingle | Junjie Liu Hui Wang Xue Li Kai Chen Chaoyu Li Robotic arm trajectory optimization based on multiverse algorithm Mathematical Biosciences and Engineering trajectory planning optimization algorithm optimal time optimal energy consumption optimal impact |
| title | Robotic arm trajectory optimization based on multiverse algorithm |
| title_full | Robotic arm trajectory optimization based on multiverse algorithm |
| title_fullStr | Robotic arm trajectory optimization based on multiverse algorithm |
| title_full_unstemmed | Robotic arm trajectory optimization based on multiverse algorithm |
| title_short | Robotic arm trajectory optimization based on multiverse algorithm |
| title_sort | robotic arm trajectory optimization based on multiverse algorithm |
| topic | trajectory planning optimization algorithm optimal time optimal energy consumption optimal impact |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2023130?viewType=HTML |
| work_keys_str_mv | AT junjieliu roboticarmtrajectoryoptimizationbasedonmultiversealgorithm AT huiwang roboticarmtrajectoryoptimizationbasedonmultiversealgorithm AT xueli roboticarmtrajectoryoptimizationbasedonmultiversealgorithm AT kaichen roboticarmtrajectoryoptimizationbasedonmultiversealgorithm AT chaoyuli roboticarmtrajectoryoptimizationbasedonmultiversealgorithm |