Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
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
Cooperative Mobile Robotics: Antecedents and Directions
Autonomous Robots
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
Human-robot interaction in rescue robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Map exploration is a fundamental problem in mobile robots. This paper presents a distributed algorithm that coordinates a team of autonomous mobile robots to explore an unknown environment. The proposed strategy is based on frontiers which are the regions on the boundary between open and unexplored space. With this strategy, robots are guided to move constantly to the nearest frontier to reduce the size of unknown region. Based on the Particle Swarm Optimization PSO model incorporated in the algorithm, robots are navigated towards remote frontier after exploring the local area. The exploration completes when there is no frontier cell in the environment. The experiments implemented on both simulated and real robot scenarios show that the proposed algorithm is capable of completing the exploration task. Compared to the conventional method of randomly selecting frontier, the proposed algorithm proves its efficiency by the decreased 60% exploration time at least. Additional experimental results show the decreased coverage time when the number of robots increases, which further suggests the validity, efficiency and scalability.