Cooperative mobile robotics: antecedents and directions
Robot colonies
Frontier-based exploration using multiple robots
AGENTS '98 Proceedings of the second 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
A frontier-based approach for autonomous exploration
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Robots: Bringing Intelligent Machines to Life
Robots: Bringing Intelligent Machines to Life
Distributed multi-robot coordination in area exploration
Robotics and Autonomous Systems
Distributed multi-robot coordination in area exploration
Robotics and Autonomous Systems
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 04
Robotic path planning using multi neuron heuristic search
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning
Artificial Intelligence Review
Coordinated multi-robot exploration
IEEE Transactions on Robotics
Human-robot interaction in rescue robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Area exploration is the key behind many researches in robotics. Numerous exploration problems have been solved based on the concept of frontiers that can be defined as the boundary between the explored and unexplored cell. In this paper we considered the problem of energy efficient exploration with a team of robots. An approach has been proposed that chooses the next frontier based on the direction strategy which simultaneously takes into account the location of other robot as well. Whenever a frontier has to be assigned to a specific robot, the utility of the unexplored area visible from this position is increased so that at a time not more than single robot moves to the same cell. Based on the direction penalty is calculated for each target points. Then the frontier having minimum utility and penalty has been chosen as the next target point. The robot moves to that frontier cell using energy efficient A* algorithm. The energy efficient A* gives optimal results taking into account energy consumed for stops and turns. Java based platform is used to run the simulation. Proposed algorithm has been tested on various test maps. The result shows that our technique accomplishes the mission quickly as compared to single robot energy efficient exploration and effectively distributes the robots over the environment.