Risky Planning on Probabilistic Costmaps for Path Planning in Outdoor Environments

Journal article

This paper presents a framework for path planning over probabilistic costmaps of outdoor terrain that is compatible with fast grid-based planners such as A*and D*. We begin with an exemplar of how probabilistic costmaps may be constructed and then show how the a priori availability of such maps lends itself to the precomputation of exact probabilistic heuristics. In turn, the probabilistic nature of these heuristics allow the user to employ a bounded speed-accuracy tradeoff that characterizes the risk of paths returned not being of optimal shortest-path length. Results are shown which demonstrate that the method is able to closely approximate a probability distribution over the underlying exact distance and that efficiency increases on the order of 90% in terms of nodes expanded, and 60% in terms of search time over Euclidean distance heuristics, can be achieved. © 2004-2012 IEEE.

Authors: Murphy, L; Newman, P

• Publication status: Published
• Journal: IEEE TRANSACTIONS ON ROBOTICS
• Volume: 29
• Issue: 2
• Pages: 445-457
• Publication date: 2013-04-01
• DOI: 10.1109/TRO.2012.2227216
• EISSN: 1941-0468
• ISSN: 1552-3098
• Language: English
• Keywords: Probabilistic planning