This paper describes a method of modeling the motion uncertainty of moving obstacles and its application to mobile robot motion planning. The method explicitly considers three sources of uncertainty: path ambiguity, velocity uncertainty, and observation uncertainty. The uncertainty model represents the position of an obstacle at a certain time point by a probabilistic distribution over possible positions on each possible path of the moving obstacle. Using this model, the best robot motion is selected in a decisiontheoretic way. By considering not the range but the distribution of the uncertainty, more efficient behaviors of the robot are realized.
['Jun Miura', 'Yoshiaki Shirai']
Probabilistic Uncertainty Modeling of Obstacle Motion for Robot Motion Planning