{"type":"ScholarlyArticle","title":"Maintaining Communication in Multi-Robot Tree Coverage","authors":[{"name":"Mor Sinay","slug":"mor-sinay","given":"Mor","family":"Sinay","affiliation":"Bar-Ilan University , Israel"},{"name":"Noa Agmon","slug":"noa-agmon","given":"Noa","family":"Agmon","affiliation":"Bar-Ilan University , Israel"},{"name":"Oleg Maksimov","slug":"oleg-maksimov","given":"Oleg","family":"Maksimov","affiliation":"Bar-Ilan University , Israel"},{"name":"Sarit Kraus","slug":"sarit-kraus","given":"Sarit","family":"Kraus","affiliation":"Bar-Ilan University , Israel"},{"name":"David Peleg","slug":"david-peleg","given":"David","family":"Peleg","affiliation":"The Weizmann Institute , Israel"}],"abstract":"Area coverage is an important task for mobile robots, mainly due to its applicability in many domains, such as search and rescue. In this paper we study the problem of multi-robot coverage, in which the robots must obey a strong communication restriction: they should maintain connectivity between teammates throughout the coverage. We formally describe the Multi-Robot Connected Tree Coverage problem, and an algorithm for covering perfect N-ary trees while adhering to the communication requirement. The algorithm is analyzed theoretically, providing guarantees for coverage time by the notion of speedup factor. We enhance the theoretically-proven solution with a dripping heuristic algorithm, and show in extensive simulations that it significantly decreases the coverage time. The algorithm is then adjusted to general (not necessarily perfect) N-ary trees and additional experiments prove its efficiency. Furthermore, we show the use of our solution in a simulated officebuilding scenario. Finally, we deploy our algorithm on real robots in a real office building setting, showing efficient coverage time in practice.","doi":"10.24963/ijcai.2017/630","url":"https://ijcai.org/proceedings/2017/630","pdf":"https://ijcai.org/proceedings/2017/0630.pdf","markdown":"https://ijcai.org/proceedings/2017/630.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/630","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Robotics and Vision","track":"Main track","number":630,"pages":{"first":4515,"last":4522},"keywords":["Robotics and Vision: Motion and Path Planning","Robotics and Vision: Multi-Robot Systems"],"videos":[],"references":[{"position":1,"raw":"[Banfi et al., 2016] Jacopo Banfi, Alberto Quattrini Li, Nicola Basilico, Ioannis Rekleitis, and Francesco Amigoni. 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