Maintaining communication in multi-robot tree coverage

Mor Sinay, Noa Agmon, Oleg Maksimov, Sarit Kraus, David Peleg

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


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.

Original languageEnglish
Title of host publication26th International Joint Conference on Artificial Intelligence, IJCAI 2017
EditorsCarles Sierra
Number of pages8
ISBN (Electronic)9780999241103
StatePublished - 2017
Event26th International Joint Conference on Artificial Intelligence, IJCAI 2017 - Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence


Conference26th International Joint Conference on Artificial Intelligence, IJCAI 2017

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence


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