@conference {418,
	title = {A Search-Based Approach to Solve Pursuit-Evasion Games with Limited Visibility in Polygonal Environments},
	booktitle = {International Conference on Autonomous \& Multiagent Systems (AAMAS)},
	year = {2018},
	url = {http://dl.acm.org/citation.cfm?id=3237383.323795},
	author = {Quattrini Li, Alberto and Raffaele Fioratto and Francesco Amigoni and Volkan Isler}
}
@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}
}
@conference {332,
	title = {Multirobot Exploration for Building Communication Maps with Prior from Communication Models},
	booktitle = {Proceedings of the International Symposium on Multi-Robot and Multi-Agent Systems (MRS)},
	year = {2017},
	author = {Phani Krishna Penumarthi and Quattrini~Li, Alberto and Jacopo Banfi and Nicola Basilico and Francesco Amigoni and Jason O{\textquoteright}Kane and Ioannis Rekleitis and Srihari Nelakuditi}
}
@conference {333,
	title = {Multirobot Online Construction of Communication Maps},
	booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2017},
	abstract = {The importance of communication in many multirobot information-gathering tasks requires the availability of reliable communication maps. These provide estimates of the radio signal strength and can be used to predict the presence of communication links between different locations of the environment. In the problem we consider, a team of mobile robots has to build such maps autonomously in a robot-to-robot communication setting. The solution we propose models the signal{\textquoteright}s distribution with a Gaussian Process and exploits different online sensing strategies to coordinate and guide the robots during their data acquisition. Our methods show interesting operative insights both in simulations and on real TurtleBot 2 platforms.},
	doi = {10.1109/ICRA.2017.7989300},
	author = {Jacopo Banfi and Quattrini~Li, Alberto and Nicola Basilico and Ioannis Rekleitis and Francesco Amigoni}
}
@conference {171,
	title = {Asynchronous Multirobot Exploration under Recurrent Connectivity Constraints},
	booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2016},
	address = {Stockholm, Sweden},
	abstract = {In multirobot exploration under centralized control, communication plays an important role in constraining the team exploration strategy. Recurrent connectivity is a way to define communication constraints for which robots must
connect to a base station only when making new observations.
This paper studies effective multirobot exploration strategies under recurrent connectivity by considering a centralized and
asynchronous planning framework. We formalize the problem of selecting the optimal set of locations robots should reach, provide an exact formulation to solve it, and devise an approximation algorithm to obtain efficient solutions with a bounded loss of optimality. Experiments in simulation and on real robots
evaluate our approach in a number of settings.},
	author = {Jacopo Banfi and Alberto Quattrini~Li and Nicola Basilico and Ioannis Rekleitis and Francesco Amigoni}
}
@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}
}
