Journal of System Simulation
Abstract
Abstract: To optimize the working trajectory of the robotic arm, a modified simulated annealing genetic algorithm is proposed. Comprehensively considering the operating requirements and performance characteristics of the robotic arm, the five-order polynomial interpolation method is used to plan a smooth motion trajectory in the joint space. The penalty function method is used to handle the individuals that do not meet the constraint conditions, and the fitness function is recalibrated by the dynamic linear calibration method. An adaptive adjustment mechanism for crossover probability and variation probability is set to modify the genetic algorithm. The cooling idea of the simulated annealing algorithm is introduced, which effectively avoids the algorithm falling into locally optimal. The results show that the optimized trajectory of the improved simulated annealing genetic algorithm effectively shortens the movement time of the robotic arm compared with the traditional genetic algorithm, and then improves the working efficiency of the robotic arm.
Recommended Citation
Xu, Qiang; Xu, Jianlei; Hu, Yanhai; Chen, Haihui; Zhang, Xing; and Xing, Zhaohui
(2025)
"Trajectory Optimization of Robotic Arm Based on Improved Simulated Annealing Genetic Algorithm,"
Journal of System Simulation: Vol. 37:
Iss.
2, Article 8.
DOI: 10.16182/j.issn1004731x.joss.23-1148
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss2/8
First Page
404
Last Page
412
CLC
TP242; TP391.9
Recommended Citation
Xu Qiang, Xu Jianlei, Hu Yanhai, et al. Trajectory Optimization of Robotic Arm Based on Improved Simulated Annealing Genetic Algorithm[J]. Journal of System Simulation, 2025, 37(2): 404-412.
DOI
10.16182/j.issn1004731x.joss.23-1148
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons