Title
Coordinated multi-robot exploration through unsupervised clustering of unknown space
Abstract
This paper proposes a new coordination algorithm for efficiently exploring an unknown environment with a team of mobile robots. The proposed technique subsequently applies a well-known unsupervised clustering algorithm (k-means) in order to fairly divide the remaining unknown space into as many disjoint regions as available robots. Each robot is primarily responsible for exploring its assigned region and can help other robots on its way through. Unknown space is dynamically repartitioned as new areas are discovered by the team, balancing thus the overall workload among team members and naturally leading to greater dispersion over the environment and thus faster broad coverage than with previous greedy-like approaches, which guide robots based on maximum profit strategies that simply trade off between distance to the closest frontiers and amount of unknown cells likely to be discovered from them.
Year
DOI
Venue
2004
10.1109/IROS.2004.1389437
IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference
Keywords
Field
DocType
intelligent robots,mobile robots,multi-robot systems,pattern clustering,coordinated multirobot exploration,mobile robots,unsupervised clustering algorithm
Robot control,Computer vision,Disjoint sets,Computer science,Pattern clustering,Workload,Intelligent robots,Artificial intelligence,Cluster analysis,Robot,Mobile robot,Machine learning
Conference
Volume
ISBN
Citations 
1
0-7803-8463-6
26
PageRank 
References 
Authors
1.23
9
2
Name
Order
Citations
PageRank
Agusti Solanas168750.73
Miguel Ángel Garcia222024.41