Title:
Planning with Movable Obstacles in Continuous Environments with Uncertain Dynamics
Planning with Movable Obstacles in Continuous Environments with Uncertain Dynamics
Author(s)
Levihn, Martin
Scholz, Jonathan
Stilman, Mike
Scholz, Jonathan
Stilman, Mike
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Abstract
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.
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Date Issued
2013-05
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Post-print
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