@article {411,
	title = {Multi-robot online sensing strategies for the construction of communication maps},
	journal = {Autonomous Robots},
	volume = {44},
	year = {2020},
	month = {Jan-03-2020},
	pages = {299 - 319},
	abstract = {This paper tackles the problem of constructing a communication map of a known environment using multiple robots. A communication map encodes information on whether two robots can communicate when they are at two arbitrary locations and plays a fundamental role for a multi-robot system deployment to reliably and effectively achieve a variety of tasks, such as environmental monitoring and exploration. Previous work on communication map building typically considered only scenarios with a fixed base station and designed offline methods, which did not exploit data collected online by the robots. This paper proposes Gaussian Process-based online methods to efficiently build a communication map with multiple robots. Such robots form a mesh network, where there is no fixed base station. Specifically, we provide two leader-follower online sensing strategies to coordinate and guide the robots while collecting data. Furthermore, we improve the performance and computational efficiency by exploiting prior communication models that can be built from the physical map of the environment. Extensive experimental results in simulation and with a team of TurtleBot 2 platforms validate the approach.},
	keywords = {Communication maps, Multi-robot systems, Sensing strategies},
	issn = {0929-5593},
	doi = {10.1007/s10514-019-09862-3},
	url = {http://link.springer.com/10.1007/s10514-019-09862-3},
	author = {Quattrini~Li, Alberto and Penumarthi, Phani Krishna and Banfi, Jacopo and Basilico, Nicola and O{\textquoteright}Kane, Jason M. and Rekleitis, Ioannis and Nelakuditi, Srihari and Amigoni, Francesco}
}
@book {414,
	title = {Online Update of Communication Maps for Exploring Multirobot Systems Under Connectivity Constraints},
	series = {Springer Proceedings in Advanced Robotics - Distributed Autonomous Robotic Systems},
	volume = {9},
	year = {2019},
	pages = {513 - 526},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	keywords = {Communication, Exploration, Multirobot systems},
	isbn = {978-3-030-05815-9},
	issn = {2511-1256},
	doi = {10.1007/978-3-030-05816-610.1007/978-3-030-05816-6_36},
	url = {http://link.springer.com/10.1007/978-3-030-05816-6},
	author = {Amigoni, Francesco and Banfi, Jacopo and Basilico, Nicola and Rekleitis, Ioannis and Quattrini~Li, Alberto},
	editor = {Correll, Nikolaus and Schwager, Mac and Otte, Michael}
}
@conference {212,
	title = {Minimizing communication latency in multirobot situation-aware patrolling},
	booktitle = {Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on},
	year = {2015},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Banfi, Jacopo and Basilico, Nicola and Amigoni, Francesco}
}
@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}
}
