Trajectory Planning of Manipulators Based on Artificial Immune-improved Particle Swarm Optimization Algorithm
The trajectory of the welding robot is complex and the control accuracy is high. A trajectory planning method is proposed to meet the multi-objective constraints. Aiming at the requirement of robot trajectory smoothness, the Cartesian space waypoints are parameterized based on the quintic non-unifor...
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| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2024-05-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.05.005 |
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| Summary: | The trajectory of the welding robot is complex and the control accuracy is high. A trajectory planning method is proposed to meet the multi-objective constraints. Aiming at the requirement of robot trajectory smoothness, the Cartesian space waypoints are parameterized based on the quintic non-uniform rational B-splines (NURBS) curve. Based on the path constraints and operational requirements of industrial robots, three kinematic indicators of time, energy consumption, and jump are selected as the objective optimization functions, and artificial immune bimodal particle swarm is used for trajectory optimization. In order to balance the exploration and utilization of particles, a bimodal model is added, and an artificial immune system is introduced to increase the particle diversity and the later convergence ability. According to the Pareto solution set, the optimal trajectory of each joint of the welding robot satisfying the constraints is obtained, and the effectiveness of the method is proved by Matlab simulation. The results show that the planned trajectory meets the actual engineering requirements. |
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| ISSN: | 1004-2539 |