A numerical technique for planning motion strategies of a mobile robot in presence of uncertainty

This paper addresses the problem of planning the motions of a circular mobile robot moving amidst polygonal obstacles with uncertainty in robot control and sensing. The robot is equipped with sensors which, if properly used, may provide information to overcome the uncertainty accumulated during the motions. The position sensor is based on dead-reckoning, the error then results in a cumulative uncertainty. A proximity sensor may be used to localize the robot with respect to the obstacles of the environment. The robot can also gain information by entering inside landmark areas where the position error is assumed to be bounded. The authors describe a planner which produces robust motion strategies composed of sensor-based motion commands which guarantee that, given an explicit model of the error accumulated by the motion commands, the robot can reach safely its goal with an error lower than a pre-specified value. It is based on a propagation of a numerical potential and on a geometric analysis of the reachability of environmental features. This planner exhibits a set of powerful capabilities: while it allows motion primitives which accumulate uncertainty to be considered, it is able, whenever possible, to navigate without relocalizing the robot when the task does not impose it, and also to make a proper use of the sensors. Several examples run with the planner are presented.