Locally efficient path planning in an uncertain, dynamic environment using a probabilistic model

The problem addressed is that of efficiently planning a path for a robot between two points when the path is forced to change dynamically by the occurrence of certain events in the environment. An event or an alarm, for example, may be the discovery of another moving object on a collision course with the robot and would require some evasive action. A probabilistic model is given that represents the robot's dynamic behavior in response to alarms that have a Poisson distribution, and safety rules that assume that some regions are safe. A provably optimal expected solution for the problem is given, and the variation of the optimal path with two parameters that represent the alarm rate and the safety rule, respectively, is discussed. >