Moving Obstacle Avoidance for the Mobile Robot using the Probabilistic Inference

In this paper, we present a motion planning algorithm using the probabilistic inference for the mobile robot. This study aim is for the mobile robot to avoid the moving obstacle and to reach the target position. The proposal algorithm consists of three steps. In the first step, robot system predicts the trajectory of the moving obstacle. Prediction is performed as what the moving obstacle follows to tangential direction by the proposal algorithm. In the second step, robot system calculates the prediction region of the moving obstacle. Mathematical model that is based on the probability density function of two-dimensional normal distribution is used in prediction region. In the third step, robot system plans the mobile robot motion. The potential field method is used in the motion planning for the mobile robot. The proposal algorithm was investigated by simulations in order to be effective. By simulations, we tested whether the mobile robot can avoid the moving obstacle and reach the target position. The mobile robot can avoid the moving obstacle was confirmed by simulation results.