@conference {416,
	title = {Heterogeneous Multirobot System for Exploration and Strategic Water Sampling},
	booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2018},
	url = {https://doi.org/10.1109/ICRA.2018.8460759},
	author = {Sandeep Manjanna and Quattrini~Li, Alberto and Ryan N. Smith and Ioannis Rekleitis and Gregory Dudek}
}
@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}
}
@mastersthesis {23,
	title = {Heterogeneous Multi-Robot Cooperation},
	volume = {PhD},
	year = {1994},
	month = {02/1994},
	url = {ftp://publications.ai.mit.edu/ai-publications/1000-1499/AITR-1465/},
	author = {Lynne E. Parker}
}
