D. Schulz, and W. Burgard
Probabilistic State Estimation
of Dynamic Objects with a Moving Mobile Robot
Robotics and Autonomous Systems
Abstract
Mobile service robots are designed to operate in dynamic and populated
environments. To plan their missions and to perform them successfully,
mobile robots need to keep track of relevant changes in the environment.
For example, office delivery
or cleaning robots must be able to estimate the state of doors or the
position of waste-baskets in order to deal with the dynamics of the environment.
In this paper we present a probabilistic technique for estimating the state
of dynamic objects in
the environment of a mobile robot. Our method matches real sensor measurements
against expected measurements obtained by a sensor simulation to efficiently
and accurately identify the most likely state of each object even if the
robot is in
motion. The probabilistic approach allows us to incorporate the robot's
uncertainty in its position into the state estimation process. The method
has been implemented and tested on a real robot. We present different examples
illustrating the
efficiency and robustness of our approach.
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Bibtex
@Article{Sch00Pro,
author = {Schulz, D. and Burgard, W.},
title = {Probabilistic State Estimation of Dynamic
Objects with a Moving Mobile Robot},
journal = {Robotics and Autonomous Systems},
volume = 34,
number = {2-3},
year = 2001
}