Path Planning for Coalmine Rescue Robot Based on Hybrid Adaptive Artificial Fish Swarm Algorithm

Yao Zheng-Hua, Ren Zi-Hui, Zhu Xian-Hua, Li Shi-Chun


For the problem with imprecise optimal solution and reduced convergence efficiency of basic artificial fish swarm algorithm (BAFSA) in the late, the adaptive enhanced prey behavior of artificial fish and the segmented adaptive strategy of artificial fish’s view and step were designed. The hybrid adaptive artificial fish swarm algorithm (HAAFSA) was structured by the adaptive enhanced prey behavior and the segmented adaptive strategy of artificial fish’s view and step, which has been verified on research. According to the characteristics of the coalmine rescue environment, the path planning environment model was established in two-dimensional plane and the optimization constraints conditions were disposed by detecting the distance between path sections and barriers. The HAAFSA was applied to coalmine rescue robot path planning. Simulation results showed that the HAAFSA could improve the performance of the optimal path.


AFSA, path planning, enhanced prey, segmented adaption, rescue robot

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