TY - GEN
T1 - Maintaining communication in multi-robot tree coverage
AU - Sinay, Mor
AU - Agmon, Noa
AU - Maksimov, Oleg
AU - Kraus, Sarit
AU - Peleg, David
N1 - Funding Information: ∗This research was supported in part by a grant from the Ministry of Science & Technology, Israel & the Japan Science and Technology Agency (jst), Japan & ISF grant #1337/15.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85031936603&partnerID=8YFLogxK
U2 - 10.24963/ijcai.2017/630
DO - 10.24963/ijcai.2017/630
M3 - منشور من مؤتمر
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 4515
EP - 4522
BT - 26th International Joint Conference on Artificial Intelligence, IJCAI 2017
A2 - Sierra, Carles
T2 - 26th International Joint Conference on Artificial Intelligence, IJCAI 2017
Y2 - 19 August 2017 through 25 August 2017
ER -