Intelligence without representation
Artificial Intelligence
Communication in reactive multiagent robotic systems
Autonomous Robots
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
Coordinated multi-robot exploration
IEEE Transactions on Robotics
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Although explicit coordination of team search may provide solid performance for small team sizes, it has been shown that such methods do not scale to larger teams due to limited communications bandwidth and computational requirements. In addition, methods that rely upon persistent, reliable network connections may have limited applicability to real-world search problems. In this work, we explore implicit cooperation enabled through sharing of search progress information. Prior research shows cooperation paradigms in which team members share a global task list result in interference and duplication of search when members choose the same search areas. Methods that only use local sensor information to identify search targets require fewer message exchanges and create less interference between robots than existing shared approaches. In addition, search progress and completion are more consistent due to the reduction in interference. Results based on simulations and physical experiments are presented that compare performance in terms of time-to-cover, consistency, and interference.