Planning with movable obstacles in continuous environments with uncertain dynamics


In this paper we present a decision theoretic planner for the problem of Navigation Among Movable Obstacles (NAMO) operating under conditions faced by real robotic systems. While planners for the NAMO domain exist, they typically assume a deterministic environment or rely on discretization of the configuration and action spaces, preventing their use in practice. In contrast, we propose a planner that operates in real-world conditions such as uncertainty about the parameters of workspace objects and continuous configuration and action (control) spaces. To achieve robust NAMO planning despite these conditions, we introduce a novel integration of Monte Carlo simulation with an abstract MDP construction. We present theoretical and empirical arguments for time complexity linear in the number of obstacles as well as a detailed implementation and examples from a dynamic simulation environment.

DOI: 10.1109/ICRA.2013.6631116

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@article{Levihn2013PlanningWM, title={Planning with movable obstacles in continuous environments with uncertain dynamics}, author={Martin Levihn and Jonathan Scholz and Mike Stilman}, journal={2013 IEEE International Conference on Robotics and Automation}, year={2013}, pages={3832-3838} }