A framework for motion planning in stochastic environments: applications and computational issues

Abstract

The authors (1995) have previously presented a framework for analyzing motion plans for a robot that operates in an environment that changes over time in an uncertain manner. In this paper, the authors demonstrate the utility of their framework by applying it to a variety of motion planning problems. Examples are computed for problems that involve a changing configuration space, hazardous regions and shelters, and processing of random service requests. To achieve this, the authors have exploited the powerful principle of optimality, which leads to a dynamic programming-based algorithm for determining optimal strategies. Several computed examples are presented and discussed.