@conference {37,
	title = {Coverage search in 3D},
	booktitle = {Proc. of the {IEEE} Int. Workshop on Safety, Security and Rescue Robotics {(SSRR)},
	year = {2013},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Linkoeping, Sweden},
	abstract = {Searching with a sensor for objects and to observe parts of a known environment efficiently is a fundamental problem in many real-world robotic applications such as household robots searching for objects, inspection robots searching for leaking pipelines, and rescue robots searching for survivors after a disaster. We consider the problem of identifying and planning efficient view point sequences for covering complex 3d environments. We compare empirically several variants of our algorithm that allow to trade-off schedule computation against execution time. Our results demonstrate that, despite the intractability of the overall problem, computing effective solutions for coverage search in real 3d environments is feasible.},
	keywords = {3D environments, coverage search, Educational institutions, execution time, household robots, image sequences, inspection robots, leaking pipelines search, objects search, path planning, Planning, rescue robots, Robot sensing systems, robot vision, robotic applications, schedule computation, Search problems, sensor, service robots, solid modelling, survivors search, Three-dimensional displays, Traveling salesman problems, view point sequences},
	doi = {10.1109/SSRR.2013.6719340},
	author = {Dornhege, C. and Kleiner, A. and Kolling, A.}
}
@conference {36,
	title = {Coverage search in 3D},
	year = {2013},
	address = {Linkoeping, Sweden},
	abstract = {Searching with a sensor for objects and to observe parts of a known environment efficiently is a fundamental problem in many real-world robotic applications such as household robots searching for objects, inspection robots searching for leaking pipelines, and rescue robots searching for survivors after a disaster. We consider the problem of identifying and planning efficient view point sequences for covering complex 3d environments. We compare empirically several variants of our algorithm that allow to trade-off schedule computation against execution time. Our results demonstrate that, despite the intractability of the overall problem, computing effective solutions for coverage search in real 3d environments is feasible.},
	keywords = {3D environments, coverage search, Educational institutions, execution time, household robots, image sequences, inspection robots, leaking pipelines search, objects search, path planning, Planning, rescue robots, Robot sensing systems, robot vision, robotic applications, schedule computation, Search problems, sensor, service robots, solid modelling, survivors search, Three-dimensional displays, Traveling salesman problems, view point sequences},
	doi = {10.1109/SSRR.2013.6719340},
	author = {Dornhege, C. and Kleiner, A. and Kolling, A.}
}
@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.}
}
@article {180,
	title = {Multiple Traveling Robot Problem: A Solution Based on Dynamic Task Selection and Robust Execution},
	journal = {Mechatronics, IEEE/ASME Transactions on},
	volume = {14},
	year = {2009},
	pages = {198-206},
	keywords = {Distributed multirobot task allocation, dynamic task selection scheme, incremental task allocation, incremental task selection, mobile robots, Multi-robot systems, multiple traveling robot problem, multiple traveling robot problem (MTRP), NP-hard multiple traveling salesman problem, path planning, priority-based rough schedules, Robust Control, robust execution, robustness, travelling salesman problems},
	issn = {1083-4435},
	doi = {10.1109/TMECH.2009.2014157},
	author = {Sanem Sariel-Talay and Tucker R. Balch and Nadia Erdogan}
}
