To enhance the path planning capability of material transfer robots during shop-floor operations, an improved path planning method with particle swarm and ant colony algorithms based on the characteristics of materials is proposed. First, the improved particle swarm grouping method containing elite subpopulations is proposed to increase the population diversity and solve the following problem: the algorithm is easy to fall into the local optimum. Moreover, the parameters are adaptively adjusted to enhance the particle search ability. Second, a bidirectional search strategy is utilized to enhance ant utilization and optimize the algorithm`s speed. Finally, a marking grid is set to enhance the safety of the robot operation, and the path is smoothed using cubic B-spline curves, thereby reducing the robot`s energy consumption. The simulation results reveal that the algorithm can effectively enhance path-planning efficiency and provide a basis for further research on the application of robot path-planning algorithms for material transfer in shop-floor environments.
Material transfer robots, Characteristics of materials, Particle swarm grouping, Elite subpopulations.
Yan HAN, Tao SONG, "Path Planning for Shop-Floor Material Transfer Robots Incorporating Particle Swarm and Ant Colony Algorithms", Studies in Informatics and Control, ISSN 1220-1766, vol. 33(3), pp. 49-59, 2024. https://doi.org/10.24846/v33i3y202405
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