Mobile robot path planning method based on multi-core search improved grey wolf algorithm

The invention provides a mobile robot path planning method based on a multi-core search improved grey wolf algorithm. The method comprises the following steps of acquiring a robot moving area map; according to the robot moving area map, establishing a target function for path planning of the moving area map; based on a grey wolf algorithm, initializing a grey wolf population position through Singer mapping, calculating a fitness value according to an objective function, and determining an optimal grey wolf position; updating the gray wolf position by adopting a multi-core search mode, and determining the updated optimal fitness value and the optimal gray wolf position; performing lens reverse learning on the optimal gray wolf position to obtain an updated optimal fitness value and an optimal gray wolf position, and taking the gray wolf position with the optimal fitness value before and after learning as the updated optimal gray wolf position; and determining an optimal path planning result according to the optimal gray wolf positions which are sequentially updated according to a preset maximum iteration number. According to the method, several defects of the grey wolf algorithm are overcome, and the path planning effect can be remarkably improved.