Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm
Trajectory planning of robotic manipulators in complex environments involves generating smooth and collision-free paths, and key aspects to consider include dynamic environment perception, path planning, trajectory smoothing and optimization, and obstacle avoidance. This paper discusses different al...
| Main Authors: | , , , , , , |
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| Format: | Article |
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World Scientific
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/120312/ |
| _version_ | 1848868160281772032 |
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| author | Ma, Haohao As’arry, Azizan Cong, Miaomiao Delgoshaei, Aidin Ismail, Mohd Idris Shah Ramli, Hafiz Rashidi Wu, Xuping |
| author_facet | Ma, Haohao As’arry, Azizan Cong, Miaomiao Delgoshaei, Aidin Ismail, Mohd Idris Shah Ramli, Hafiz Rashidi Wu, Xuping |
| author_sort | Ma, Haohao |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Trajectory planning of robotic manipulators in complex environments involves generating smooth and collision-free paths, and key aspects to consider include dynamic environment perception, path planning, trajectory smoothing and optimization, and obstacle avoidance. This paper discusses different algorithms and finally proposes a fusion of the improved Dung Beetle Optimizer (IDBO) algorithm using chaotic mapping, sinusoidal random mutation, and nonlinear convergence strategies with the bidirectional Rapidly exploring Random Tree (RRT) algorithm to achieve manipulator trajectory planning and minimum jerk optimization trajectory. In the experiment, the IDBO algorithm was compared with other heuristic algorithms. The path obtained was shortened by 9.18% on average, and the calculation time was shortened by 33.81% on average. Then, the paper explored Cartesian coordinate space trajectory planning and joint space trajectory planning when the robot was working in 3D space, and verified the superiority of the latter. In controlling the movement of the robot, by combining the minimum angle jerk planning and the bidirectional RRT obstacle avoidance algorithm to drive the joint angle parameters obtained by the spatial trajectory planning, the trajectory of the robot manipulator can be smoother, more efficient, and avoid obstacles in complex 3D space. This research helps improve the performance, safety, and technical support of robots, and is of great research significance. |
| first_indexed | 2025-11-15T14:47:58Z |
| format | Article |
| id | upm-120312 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T14:47:58Z |
| publishDate | 2024 |
| publisher | World Scientific |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1203122025-10-05T18:15:56Z http://psasir.upm.edu.my/id/eprint/120312/ Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm Ma, Haohao As’arry, Azizan Cong, Miaomiao Delgoshaei, Aidin Ismail, Mohd Idris Shah Ramli, Hafiz Rashidi Wu, Xuping Trajectory planning of robotic manipulators in complex environments involves generating smooth and collision-free paths, and key aspects to consider include dynamic environment perception, path planning, trajectory smoothing and optimization, and obstacle avoidance. This paper discusses different algorithms and finally proposes a fusion of the improved Dung Beetle Optimizer (IDBO) algorithm using chaotic mapping, sinusoidal random mutation, and nonlinear convergence strategies with the bidirectional Rapidly exploring Random Tree (RRT) algorithm to achieve manipulator trajectory planning and minimum jerk optimization trajectory. In the experiment, the IDBO algorithm was compared with other heuristic algorithms. The path obtained was shortened by 9.18% on average, and the calculation time was shortened by 33.81% on average. Then, the paper explored Cartesian coordinate space trajectory planning and joint space trajectory planning when the robot was working in 3D space, and verified the superiority of the latter. In controlling the movement of the robot, by combining the minimum angle jerk planning and the bidirectional RRT obstacle avoidance algorithm to drive the joint angle parameters obtained by the spatial trajectory planning, the trajectory of the robot manipulator can be smoother, more efficient, and avoid obstacles in complex 3D space. This research helps improve the performance, safety, and technical support of robots, and is of great research significance. World Scientific 2024 Article PeerReviewed Ma, Haohao and As’arry, Azizan and Cong, Miaomiao and Delgoshaei, Aidin and Ismail, Mohd Idris Shah and Ramli, Hafiz Rashidi and Wu, Xuping (2024) Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm. Journal of Circuits, Systems and Computers, 34 (1). art. no. 2550028. ISSN 0218-1266; eISSN: 1793-6454 https://www.worldscientific.com/doi/10.1142/S0218126625500288 10.1142/s0218126625500288 |
| spellingShingle | Ma, Haohao As’arry, Azizan Cong, Miaomiao Delgoshaei, Aidin Ismail, Mohd Idris Shah Ramli, Hafiz Rashidi Wu, Xuping Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm |
| title | Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm |
| title_full | Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm |
| title_fullStr | Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm |
| title_full_unstemmed | Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm |
| title_short | Robot manipulator minimum jerk trajectory planning based on the improved dung Beetle Optimizer Algorithm |
| title_sort | robot manipulator minimum jerk trajectory planning based on the improved dung beetle optimizer algorithm |
| url | http://psasir.upm.edu.my/id/eprint/120312/ http://psasir.upm.edu.my/id/eprint/120312/ http://psasir.upm.edu.my/id/eprint/120312/ |