@article {167,
	title = {A semantically-informed multirobot system for exploration of relevant areas in search and rescue settings},
	journal = {Autonomous Robots},
	year = {2015},
	pages = {1{\textendash}17},
	abstract = {Coordinated multirobot exploration involves autonomous discovering and mapping of the features of initially unknown environments by using multiple robots. Autonomously exploring mobile robots are usually driven, both in selecting locations to visit and in assigning them to robots, by knowledge of the already explored portions of the environment, often represented in a metric map. In the literature, some works addressed the use of semantic knowledge in exploration, which, embedded in a semantic map, associates spatial concepts (like {\textquoteleft}rooms{\textquoteright} and {\textquoteleft}corridors{\textquoteright}) with metric entities, showing its effectiveness in improving the total area explored by robots. In this paper, we build on these results and propose a system that exploits semantic information to push robots to explore relevant areas of initially unknown environments, according to a priori information provided by human users. Discovery of relevant areas is significant in some search and rescue settings, in which human rescuers can instruct robots to search for victims in specific areas, for example in cubicles if a disaster happened in an office building during working hours. We propose to speed up the exploration of specific areas by using semantic information both to select locations to visit and to determine the number of robots to allocate to those locations. In this way, for example, more robots could be assigned to a candidate location in a corridor, so the attached rooms can be explored faster. We tested our semantic-based multirobot exploration system within a reliable robot simulator and we evaluated its performance in realistic search and rescue indoor settings with respect to state-of-the-art approaches.},
	keywords = {Coordinated multirobot exploration, Search and Rescue, Semantic map},
	issn = {1573-7527},
	doi = {10.1007/s10514-015-9480-x},
	url = {http://dx.doi.org/10.1007/s10514-015-9480-x},
	author = {Quattrini~Li, Alberto and Cipolleschi, Riccardo and Giusto, Michele and Amigoni, Francesco}
}
@inbook {170,
	title = {How Much Worth Is Coordination of Mobile Robots for Exploration in Search and Rescue?},
	booktitle = {RoboCup 2012: Robot Soccer World Cup XVI},
	series = {Lecture Notes in Computer Science},
	number = {7500},
	year = {2013},
	pages = {106{\textendash}117},
	publisher = {Springer},
	organization = {Springer},
	chapter = {How Much Worth Is Coordination of Mobile Robots for Exploration in Search and Rescue?},
	address = {Berlin, Heidelberg},
	abstract = {Exploration of unknown environments is an enabling task for several applications, including map building and search and rescue. It is widely recognized that several benefits can be derived from deploying multiple mobile robots in exploration, including increased robustness and efficiency. Two main issues of multirobot exploration are the exploration strategy employed to select the most convenient observation locations the robots should reach in a partially known environment and the coordination method employed to manage the interferences between the actions performed by robots. From the literature, it is difficult to assess the relative effects of these two issues on the system performance. In this paper, we contribute to filling this gap by studying a search and rescue setting in which different coordination methods and exploration strategies are implemented and their contributions to an efficient exploration of indoor environments are comparatively evaluated. Although preliminary, our experimental data lead to the following results: the role of exploration strategies dominates that of coordination methods in determining the performance of an exploring multirobot system in a highly structured indoor environment, while the situation is reversed in a less structured indoor environment.},
	keywords = {coordination, Exploration, multirobot, Search and Rescue},
	isbn = {978-3-642-39250-4},
	doi = {10.1007/978-3-642-39250-4_11},
	url = {http://dx.doi.org/10.1007/978-3-642-39250-4_11},
	author = {Amigoni, Francesco and Basilico, Nicola and Quattrini~Li, Alberto},
	editor = {Chen, Xiaoping and Stone, Peter and Sucar, Luis Enrique and Zant, Tijn}
}
