From Ants to Birds: A Novel Bio-Inspired Approach to Online Area Coverage

Luca Giuggioli, Idan Arye, Alexandro Heiblum Robles, Gal A. Kaminka

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

9 Scopus citations

Abstract

Online coverage path planning is a canonical multi-robot task, where the objective is to minimize the time it takes for robots to visit every point in an unknown area. Two general major approaches have been explored in the literature: a stigmergic approach, inspired by ant behavior, relies on active marking of the environment. In contrast, the collaborative approach relies instead on localization, memory of positions, and global communications. In this paper, we report on a new approach, inspired by territorial bird chirping, which borrows from both previous approaches: it relies on localization and memory, but not on global communications. We provide a detailed analytic and empirical evaluation of this model.

Original languageEnglish
Title of host publicationSpringer Proceedings in Advanced Robotics
PublisherSpringer Science and Business Media B.V.
Pages31-43
Number of pages13
DOIs
StatePublished - 2018

Publication series

NameSpringer Proceedings in Advanced Robotics
Volume6
ISSN (Print)2511-1256
ISSN (Electronic)2511-1264

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG.

Funding

LG thanks the support of the Bar Ilan Robotics Consortium (BIRC) and the office of the vice president during his stay at Bar Ilan University and acknowledges discussions with Adham Sabra and Alan Winfield. The research was supported in part by ISF grant #1511/12 and EPSRC grant EP/I013717/1. As always, thanks to K. Ushi. Data Access Statement The Java code to run the stochastic simulations is openly available in the data.bris University of Bristol repository under DOI: https://doi.org/10.5523/bris.i1rl4lk2boj410h 6ui4cpblfh. Acknowledgements LG thanks the support of the Bar Ilan Robotics Consortium (BIRC) and the office of the vice president during his stay at Bar Ilan University and acknowledges discussions with Adham Sabra and Alan Winfield. The research was supported in part by ISF grant #1511/12 and EPSRC grant EP/I013717/1. As always, thanks to K. Ushi. Data Access Statement The Java code to run the stochastic simulations is openly available in the data.bris University of Bristol repository under DOI: https://doi.org/10.5523/bris.i1rl4lk2boj410h 6ui4cpblfh.

FundersFunder number
Bar Ilan Robotics Consortium
data.bris University of Bristol
Engineering and Physical Sciences Research CouncilEP/I013717/1
Israel Science Foundation1511/12

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