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Probabilistic Graph-Clear (2009)
| Venue: | In Proceedings of the IEEE International Conference on Robotics and Automation |
| Citations: | 6 - 3 self |
BibTeX
@INPROCEEDINGS{Kolling09probabilisticgraph-clear,
author = {Andreas Kolling and Stefano Carpin},
title = {Probabilistic Graph-Clear},
booktitle = {In Proceedings of the IEEE International Conference on Robotics and Automation},
year = {2009},
pages = {3508--3514}
}
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Abstract
Abstract — This paper introduces a probabilistic model for multirobot surveillance applications with limited range and possibly faulty sensors. Sensors are described with a footprint and a false negative probability, i.e. the probability of failing to report a target within their sensing range. The model implements a probabilistic extension to our formerly developed deterministic approach for modeling surveillance tasks in large environments with large robot teams known as Graph-Clear. This extension leads to a new algorithm that allows to answer new design and performance questions, namely 1) how many robots are needed to obtain a certain confidence that the environment is free from intruders, and 2) given a certain number of robots, how should they coordinate their actions to minimize their failure rate. I.
Keyphrases
failure rate multirobot surveillance application faulty sensor false negative probability certain number certain confidence probabilistic model deterministic approach new algorithm probabilistic extension sensing range large environment large robot team performance question many robot limited range new design surveillance task
