Sensor Fusion and Decision-making in the Cooperative Search by Mobile Robots

Barouch Matzliach, Irad Ben-Gal, Evgeny Kagan

Abstract

The paper addresses the problem of probabilistic search and detection of multiple targets by the group of mobile robots that are equipped by a variety of sensors and are communicating with each other at different levels. The goal is to define the trajectories of the robots in the group such that the targets are chased in minimal time. The suggested solution model follows the occupancy grid approach, and sensor fusion is implemented using a general Bayesian scheme with varying sensitivity of the sensors. The created control algorithm was verified in three settings with different levels of communication and information sharing between the robots and different levels of sensors' sensitivity. The suggested algorithms were implemented in a software simulation to analyze and compare the different policies.

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Paper Citation


in Harvard Style

Matzliach B., Ben-Gal I. and Kagan E. (2020). Sensor Fusion and Decision-making in the Cooperative Search by Mobile Robots.In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-395-7, pages 119-126. DOI: 10.5220/0008840001190126


in Bibtex Style

@conference{icaart20,
author={Barouch Matzliach and Irad Ben-Gal and Evgeny Kagan},
title={Sensor Fusion and Decision-making in the Cooperative Search by Mobile Robots},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2020},
pages={119-126},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008840001190126},
isbn={978-989-758-395-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Sensor Fusion and Decision-making in the Cooperative Search by Mobile Robots
SN - 978-989-758-395-7
AU - Matzliach B.
AU - Ben-Gal I.
AU - Kagan E.
PY - 2020
SP - 119
EP - 126
DO - 10.5220/0008840001190126