The Task Allocation and Path Planning Based on BISOM
Feifei Chen, Daqi Zhu · 2015
For the task allocation and path planning of multi-AUV (Autonomous Underwater Vehicle) system in three dimensional underwater environments with obstacles, a novel biological inspired self-organizing task allocation and path planning algorithm is proposed. Firstly, the SOM neural network (the self-organizing map) is developed to assign targets in underwater environment to a team of AUVs. The working process involves the definition of the initial neural weights of the SOM network, the rule of selecting the winner, the computation of the neighborhood function. Then, in order to solve the problem of obstacle avoidance and sharp speed jump, the biological inspired neural dynamics model (BINM) is embedded into the SOM neural network, the biological inspired neural dynamic model is used to update weights of the SOM neural network, and plan a path without sharp speed jump and obstacles. As a result, adaptive task allocation and effective path planning are achieved. Finally, to demonstrate the effectiveness of the proposed approach, simulation results are given in this paper.