Proceedings PaperIncorporating Subjective Measures In Robot Motion Planning
|Format||Member Price||Non-Member Price|
Path planning can be grossly defined as the problem of reaching a goal from a starting position, avoiding collisions and satisfying one or more optimality criteria. A prerequisite to such a plan is the availability of an occupancy map either as an a priori information or generated on-line. Recent work has shown that such information can at best be obtained within a probabilistic framework, hence exact occupancy status is never known with absolute confidence. This paper presents a formal framework for formulating path planning under uncertainty. It is shown that paths compete not just on the basis of physically measurable parameters but also on the grounds of collision risk. There emerges circumstances requiring a formulation of underlying subjective trade-offs among competing paths with the added element of risk. A set of experimental results show the actual implementation of the proposed path planner inside a certainty grid.