@article {412,
	title = {Exploration and Mapping with Groups of Robots: Recent Trends},
	journal = {Current Robotics Reports},
	year = {2020},
	month = {Sep-09-2020},
	abstract = {Purpose of Review
Multi-robot exploration{\textemdash}i.e., the problem of mapping unknown features of an environment{\textemdash}is fundamental in many tasks, including search and rescue, planetary exploration, and environmental monitoring. This article surveys recent literature with the aim at identifying current research trends, open challenges, and future directions.

Recent Findings
Since the first formalization of the exploration problem, current research has extended systems and algorithms to map 3D environments and more complex phenomena and considered real-world constraints. Deep learning-based approaches have seen some preliminary applications in decision-making.

Summary
While current research has been progressing towards systems that can work in the real world, long-term exploration in large unstructured environments with complex phenomena to map is still an open problem. This introduces opportunities for exciting research, including but not limited to generalized frameworks that bridge the gap between theory and practice, learning-based approaches, and robustness to failure and attacks, so that robots can be deployed safely in real-world environments.},
	keywords = {Exploration, Mapping, Multi-robot systems},
	doi = {10.1007/s43154-020-00030-5},
	url = {http://link.springer.com/10.1007/s43154-020-00030-5},
	author = {Quattrini~Li, Alberto}
}
@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}
}
@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 {48,
	title = {Hierarchical Visibility for Guaranteed Search in Large-Scale Outdoor Terrain},
	journal = {JAAMAS},
	volume = {26},
	year = {2013},
	pages = {1{\textendash}36},
	abstract = {Searching for moving targets in large environments is a challenging task that is relevant in several problem domains, such as capturing an invader in a camp, guarding security facilities, and searching for victims in large-scale search and rescue scenarios. The guaranteed search problem is to coordinate the search of a team of agents to guarantee the discovery of all targets. In this paper we present a self-contained solution to this problem in 2.5D real-world domains represented by digital elevation models (DEMs). We introduce hierarchical sampling on DEMs for selecting heuristically the close to minimal set of locations from which the entire surface of the DEM can be guarded. Locations are utilized to form a search graph on which search strategies for mobile agents are computed. For these strategies schedules are derived which include agent paths that are directly executable in the terrain. Presented experimental results demonstrate the performance of the method. The practical feasibility of our approach has been validated during a field experiment at the Gascola robot training site where teams of humans equipped with iPads successfully searched for adversarial and omniscient evaders. The field demonstration is the largest-scale implementation of a guaranteed search algorithm to date.},
	keywords = {Exploration, guaranteed search, HRI, Human{\textendash}robot-interaction, Moving target search, path planning, pursuit-evasion, task allocation},
	issn = {1387-2532},
	doi = {10.1007/s10458-011-9180-7},
	url = {http://dx.doi.org/10.1007/s10458-011-9180-7},
	author = {Kleiner, A. and Kolling, A. and Lewis, M. and Sycara, K.}
}
@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}
}
@article {140,
	title = {The Sensor-based Random Graph Method for Cooperative Robot Exploration},
	journal = {IEEE/ASME Transaction on Mechatronics},
	volume = {14},
	year = {2009},
	month = {04/2009},
	pages = {163-175},
	abstract = {We present a decentralized cooperative exploration strategy for a team of mobile robots equipped with range finders. A roadmap of the explored area, with the associate safe region, is built in the form of a Sensor-based Random Graph (SRG). This is expanded by the robots by using a randomized local planner which automatically realizes a trade-off between information gain and navigation cost. The nodes of the SRG represent view configurations that have been visited by at least one robot, and are connected by arcs that represent safe paths. These paths have been actually traveled by the robots or added to the SRG to improve its connectivity. Decentralized cooperation and coordination mechanisms are used so as to guarantee exploration efficiency and avoid conflicts. Simulations and experiments are presented to show the performance of the proposed technique.},
	keywords = {Coverage, Distributed algorithms, Exploration, Multi-robot systems},
	author = {Antonio Franchi and Luigi Freda and Giuseppe Oriolo and Marilena Vendittelli}
}
