Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
Exploring unknown environments with obstacles
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
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
A frontier-based approach for autonomous exploration
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Distributed multi-robot coordination in area exploration
Robotics and Autonomous Systems
Distributed multi-robot coordination in area exploration
Robotics and Autonomous Systems
Coordinated multi-robot exploration
IEEE Transactions on Robotics
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Exploration and mapping of the environment is a critical issue in mobile robotics. In this paper we present an approach to multi-robot exploration and mapping, which is based in a distributed bidding process, where the bids are calculated by each robot. When a robot reaches the target it makes a decision by itself, which involves every one of the team members without lost of time in a totally distributed behavior and without the necessity of a central module. Furthermore, if the selected goal is discovered for another robot, this robot send a stop signal and the process of bidding is restarted.The bid is computed such each robot will be assigned to a near unexplored frontier, while keeping the robots far from each other. The bid includes the distance of robot towards one of the frontiers, and the distances to the others robots toward their objectives plus the distance of these objectives toward the frontier. The numerical results demonstrate that our approach is efficient and fault tolerant.