Path planning for optimizing survivability of multi-robot formation in adversarial environments

Yaniv Shapira, Noa Agmon

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

13 Scopus citations

Abstract

Multi robot formation is a canonical problem in robotic research. The problem has been examined in neutral environments, where the robots' goal is usually to maintain the formation despite changes in the environment. The problem of multi robot formation has been motivated by natural phenomena such as schools of fish or flocks of birds. While in the natural phenomena the team behavior is responsive to threats, in robotics research of team formation, adversarial presence has been ignored. In this paper we present the problem of adversarial formation, in which a team of robots travels in a connected formation through an adversarial environment that includes threats that may harm the robots. The robots' goal is, therefore, to maximize their chance of traveling through the environment unharmed, where the formation may be used as a mean to achieve this goal. We formally define the problem, present a quantitative measure for evaluating the survivability of the team, and suggest possible solutions to a variant of the problem under certain threat characteristics, optimizing different team survivability criteria. Finally, we discuss the challenges raised by transitioning the discrete representation to a continuous environment in simulation.

Original languageEnglish
Title of host publicationIROS Hamburg 2015 - Conference Digest
Subtitle of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4544-4549
Number of pages6
ISBN (Electronic)9781479999941
DOIs
StatePublished - 11 Dec 2015
EventIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 - Hamburg, Germany
Duration: 28 Sep 20152 Oct 2015

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2015-December
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015
Country/TerritoryGermany
CityHamburg
Period28/09/152/10/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

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