@article {331,
	title = {Strategies for coordinated multirobot exploration with recurrent connectivity constraints},
	journal = {Autonomous Robots},
	volume = {42},
	year = {2018},
	pages = {875{\textendash}894},
	abstract = {During several applications, such as search and rescue, robots must discover new information about the environment and, at the same time, share operational knowledge with a base station through an ad hoc network. In this paper, we design exploration strategies that allow robots to coordinate with teammates to form such a network in order to satisfy recurrent connectivity constraints{\textendash}-that is, data must be shared with the base station when making new observations at the assigned locations. Current approaches lack in flexibility due to the assumptions made about the communication model. Furthermore, they are sometimes inefficient because of the synchronous way they work: new plans are issued only once all robots have reached their goals. This paper introduces two novel asynchronous strategies that work with arbitrary communication models. In this paper, {\textquoteleft}asynchronous{\textquoteright} means that it is possible to issue new plans to subgroups of robots, when they are ready to receive them. First, we propose a single-stage strategy based on Integer Linear Programming for selecting and assigning robots to locations. Second, we design a two-stage strategy to improve computational efficiency, by separating the problem of locations{\textquoteright} selection from that of robot-location assignments. Extensive testing both in simulation and with real robots show that the proposed strategies provide good situation awareness at the base station while efficiently exploring the environment.},
	keywords = {Communication constraints, Exploration, Multirobot systems, Recurrent connectivity},
	doi = {10.1007/s10514-017-9652-y},
	author = {Jacopo Banfi and Quattrini~Li, Alberto and Ioannis Rekleitis and Francesco Amigoni and Nicola Basilico}
}
@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}
}
@conference {336,
	title = {Semantically-Informed Coordinated Multirobot Exploration of Relevant Areas in Search and Rescue Settings},
	booktitle = {Proceedings of the 6th European Conference on Mobile Robots (ECMR)},
	year = {2013},
	abstract = {Coordinated multirobot exploration involves autonomous discovering of unknown features in environments by using multiple robots. Autonomously exploring mobile robots are driven by knowledge of the already explored portions of the environment, usually 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 to improve total explored area. In this paper, we build on these results and propose a system that exploits semantic information to push robots to explore areas that are relevant, according to a priori information provided by human users. We tested our semantic-based multirobot exploration system in a reliable robot simulator and evaluated its performance in realistic search and rescue settings with respect to state-of-the-art approaches.},
	doi = {10.1109/ECMR.2013.6698845},
	author = {Riccardo Cipolleschi and Michele Giusto and Quattrini~Li, Alberto and Francesco Amigoni}
}
