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Ann Math Artif Intell DOI 10.1007/s10472-010-9202-1 Planning in partially-observable switching-mode continuous domains

By Emma Brunskill, Leslie Pack Kaelbling, Tomás Lozano-pérez, Nicholas Roy, E. Brunskill (b, L. P. Kaelbling, T. Lozano-pérez and N. RoyL. P. Kaelbling, T. Lozano-pérez and N. Roy

Abstract

Abstract Continuous-state POMDPs provide a natural representation for a variety of tasks, including many in robotics. However, most existing parametric continuousstate POMDP approaches are limited by their reliance on a single linear model to represent the world dynamics. We introduce a new switching-state dynamics model that can represent multi-modal state-dependent dynamics. We present the Switching Mode POMDP (SM-POMDP) planning algorithm for solving continuousstate POMDPs using this dynamics model. We also consider several procedures to approximate the value function as a mixture of a bounded number of Gaussians. Unlike the majority of prior work on approximate continuous-state POMDP planners, we provide a formal analysis of our SM-POMDP algorithm, providing bounds, where possible, on the quality of the resulting solution. We also analyze the computational complexity of SM-POMDP. Empirical results on an unmanned aerial vehicle collisions avoidance simulation, and a robot navigation simulation where the robot This research was conducted while E. Brunskill was at the Massachusett

Year: 2010
OAI identifier: oai:CiteSeerX.psu:10.1.1.170.3094
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