Research On Path Planning For Mobile Robot Based On The Biological Intelligence

This paper concentrates on the research on the path planning based on the biological intelligence. Firstly, the three common path planning methods are introduced. Secondly, the dynamic path planning for mobile robot based on improved genetic algorithm is proposed. To overcome the local optimum of genetic algorithm, the hill-climbing method is used to improve the mutation. To increase the search speed, the particle swarm optimization is used to update the colony. Thirdly, the wolf colony algorithm is proposed. A few artificial wolves are assigned to searching in the activity range of the quarry. When the searching artificial wolves discover the quarry, they notify the position of the quarry to the other artificial wolves by howl. The other artificial wolves get close to the quarry and besiege it. The wolf colony is updated according to the assignment rule of the wolf colony. Finally, the wolf colony algorithm is used to plan the optimal path for the mobile robot. The results prove that the path planning method based on the wolf colony algorithm is viable and efficient.