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Probabilistic robot navigation in partially observable environments (1995)
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| Venue: | In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI |
| Citations: | 292 - 13 self |
BibTeX
@INPROCEEDINGS{Simmons95probabilisticrobot,
author = {Reid Simmons and Sven Koenig},
title = {Probabilistic robot navigation in partially observable environments},
booktitle = {In Proc. of the International Joint Conference on Artificial Intelligence (IJCAI},
year = {1995}
}
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Abstract
Autonomous mobile robots need very reliable navigation capabilities in order to operate unattended for long periods of time. This paper reports on first results of a research program that uses partially observable Markov models to robustly track a robot’s location in office environments and to direct its goal-oriented actions. The approach explicitly maintains a probability distribution over the possible locations of the robot, taking into account various sources of uncertainty, including approximate knowledge of the environment, and actuator and sensor uncertainty. A novel feature of our approach is its integration of topological map information with approximate metric information. We demonstrate the robustness of this approach in controlling an actual indoor mobile robot navigating corridors. 1
Keyphrases
probabilistic robot navigation observable environment goal-oriented action observable markov model account various source research program topological map information robot location paper report autonomous mobile robot long period approximate knowledge novel feature approximate metric information office environment possible location reliable navigation capability actual indoor mobile robot first result sensor uncertainty probability distribution
