Multi-robot containment and disablement

Yuval Maymon, Noa Agmon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper presents the multi-robot containment and disablement (CAD) problem. In this problem, a team of (ground or aerial) robots are engaged in a cooperative task of swarm containment and disablement (for example, locust swarm). Each team member is equipped with a tool that can both detect and disable the swarm individuals. The swarm is active in a given physical location, and the goal of the robots is twofold: to contain the swarm members such that the individuals will be prevented from expanding further beyond this area (this is referred to as perfect enclosure), and to fully disable the locust by reducing the size of the contained area (while preserving the perfect enclosure). We determine the minimal number of robots necessary to ensure perfect enclosure, and a placement of the robots about the contained area such that they will be able to guarantee perfect enclosure, as well as a distributed area reduction protocol maintaining perfect enclosure. We then suggest algorithms for handling the case in which there are not enough robots to guarantee perfect enclosure, and describe their performance based on rigorous experiments in the TeamBots simulator.

Original languageEnglish
Title of host publication2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages11724-11731
Number of pages8
ISBN (Electronic)9781728162126
DOIs
StatePublished - 24 Oct 2020
Event2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020 - Las Vegas, United States
Duration: 24 Oct 202024 Jan 2021

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
Country/TerritoryUnited States
CityLas Vegas
Period24/10/2024/01/21

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

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