Frontier-based exploration using multiple robots
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Terrain coverage with ant robots: a simulation study
Proceedings of the fifth international conference on Autonomous agents
Coordination for Multi-Robot Exploration and Mapping
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Parallel Algorithms to Find the Voronoi Diagram and the Order-k Voronoi Diagram
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Building Terrain-Covering Ant Robots: A Feasibility Study
Autonomous Robots
Multi-robot exploration of an unknown environment, efficiently reducing the odometry error
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Exploring simple grid polygons
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
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We propose a Local Voronoi Decomposition (LVD) Algorithm which is able to perform a robust and online task allocation for multiple agents based purely on local information. Because only local information is required in determining each agent's Voronoi region, each agent can then make its decision in a distributive fashion based on its allocated Voronoi region. These Voronoi regions eliminates the occurrence of agents executing instantaneous overlapping tasks. As our method does not require a pre-processing of the map, it is also able to work well in a dynamically changing map with changing number of agents. We will show our proof of concept in the problem of exploration in an unknown environment. In our experimental evaluation, we show that our method significantly outperforms the competing algorithms: Ants Algorithm and the Brick&Mortar Algorithm. Our results also show that our method is near the theoretical best solution.