Modeling motion uncertainty of moving obstacles for robot motion planning

Abstract

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 motion uncertainty: path ambiguity, velocity uncertainty, and observation uncertainty. The model is represented by a probabilistic distribution over possible position an a path of a moving obstacle. Using this model, the best robot motion is selected which minimizes the expected time of reaching the destination. By considering not the range but the distribution of the uncertainty, more efficient behaviors of the robot are realized.