Coverage for robotics – A survey of recent results
Annals of Mathematics and Artificial Intelligence
Exploring artificial intelligence in the new millennium
A frontier-based approach for autonomous exploration
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Multi-objective exploration and search for autonomous rescue robots: Research Articles
Journal of Field Robotics
Adaptive multi-robot wide-area exploration and mapping
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Efficient informative sensing using multiple robots
Journal of Artificial Intelligence Research
Exploring unknown environments with mobile robots using coverage maps
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Multi-robot exploration and fire searching
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
An information-based exploration strategy for environment mapping with mobile robots
Robotics and Autonomous Systems
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Autonomous mobile robots are considered a valuable technology for search and rescue applications, where an initially unknown environment has to be explored to locate human victims. In this scenario, robots exploit exploration strategies to autonomously move around the environment. Most of the strategies proposed in literature are based on the idea of evaluating a number of candidate locations according to ad hoc utility functions that combine different criteria. In this paper, we show some of the advantages of using a more theoretically-grounded approach, based on Multi-Criteria Decision Making (MCDM), to define exploration strategies for robots employed in search and rescue applications. We implemented some MCDM-based exploration strategies within an existing robot controller and we experimentally evaluated their performance in a simulated environment.