(Georgia Institute of Technology, 2010-10)
Wu, Hai-Ning; Levihn, Martin; Stilman, Mike
This paper explores the Navigation Among Movable
Obstacles (NAMO) problem in an unknown environment.
We consider the realistic scenario in which the robot has
to navigate to a goal position in an unknown environment
consisting of static and movable objects. The robot may move
objects if the goal can not be reached otherwise or if moving
the object may significantly shorten the path to the goal.
We consider real situations in which the robot only has
limited sensing information and where the action selection
can therefore only be based on partial knowledge learned
from the environment at that point. This paper introduces an
algorithm that significantly reduces the necessary calculations
to accomplish this task compared to a direct approach. We
present an efficient implementation for the case of planar,
axis-aligned environments and report experimental results on
challenging scenarios with more than 50 objects.