A collision-free path planning for multiple mobile robots by using hopfield neural net with local range information

국소 거리정보를 얻을 수 있는 다중 이동로보트 환경에서의 Hopfield 신경회로 모델을 이용한 충돌회피 경로계획

In this paper, assuming that local range information is available, a collision-free path planning algorithm for multiple mobile robots is presented by using Hopfield neural optimization network. The energy function of the network is built using the present position and the goal position of each robot as well as its local range information. The proposed algorithm has several advantages such as the effective passing around obstacles with the directional safety distance, the easy implementation of robot motion planning including its rotation, the real-time path planning capability from the totally localized computations of path for each robot, and the adaptivity on arbitrary environment since any special shape of obstacles is not assumed.