Ant Colony Optimization Combined with Immunosuppression and Parameters Switching Strategy for Solving Path Planning Problem of Landfill Inspection Robots

[摘要] An improved ant colony optimization (ACO) combined with immunosuppression and parameters switching strategy is proposed in this paper. In this algorithm, a novel judgment criterion for immunosuppression is introduced, that is, if the optimum solution has not changed for default iteration number, the immunosuppressive strategy is carried out. Moreover, two groups of parameters in ACO are switched back and forth according to the change of optimum solution as well. Therefore, the search space is expanded greatly and the problem of the traditional ACO such as falling into local minima easily is avoided effectively. The comparative simulation studies for path planning of landfill inspection robots in Asahikawa, Japan are executed, and the results show that the proposed algorithm has better performance characterized by higher search quality and faster search speed.

[学科分类] 自动化工程

[关键词] Robots;Path Planning Improved Ant Colony Optimization;Immunosuppression;Parameters Switching Strategy