Research and Simulation on Optimal Escape Route Planning of Underwater Robot
Yin Liu · Jisuanji fangzhen · 2015
In order to guarantee the operation safety of underwater robot,an optimal escape route planning of underwater robot vision based on neural optimization network and genetic algorithm is proposed. The complex obstacle characteristics are collected by robot visual instrument to normalize to the visual information,and the planning model is integrated to make the optimal path selection. The requirements of the robot getting rid of complex obstacle and the shortest path are fused into a fitness function. The genetic algorithm is applied to search and obtain the best robot escape routes. The results of simulation show that the length and efficiency of the optimal escape route planning of underwater robot by using the neural network optimization and genetic algorithm are superior to the traditional model under the situation of dangerous and complex under sea.