@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.}
}
@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 {41,
	title = {Fast Guaranteed Search With Unmanned Aerial Vehicles},
	booktitle = {Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)},
	year = {2013},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In this paper we consider the problem of searching for an arbitrarily smart and fast evader in a large environment with a team of unmanned aerial vehicles (UAVs) while providing guarantees of detection. Our emphasis is on the fast execution of efficient search strategies that minimize the number of UAVs and the search time. We present the first approach for computing fast search strategies utilizing additional searchers to speed up the execution time and thereby enabling large scale UAV search. In order to scale to very large environments when using UAVs one would either have to overcome the energy limitations of UAVs or pay the cost of utilizing additional UAVs to speed up the search. Our approach is based on coordinating UAVs on sweep lines, covered by the UAV sensors, that move simultaneously through an environment. We present some simulation results that show a significant reduction in execution time when using multiple UAVs and a demonstration of a real system with three ARDrones.},
	keywords = {autonomous aerial vehicles;multi-robot systems;search problems;sensors;AR.Drone 2.0;UAV sensors;fast guaranteed search;search problem;search strategies;unmanned aerial vehicles;Delays;Robot kinematics;Robot sensing systems;Search problems;Surveillance},
	doi = {10.1109/IROS.2013.6697229},
	author = {Kolling, A. and Kleiner, A. and Rudol, P}
}
@conference {39,
	title = {Fast Guaranteed Search With Unmanned Aerial Vehicles},
	booktitle = {Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)},
	year = {2013},
	abstract = {In this paper we consider the problem of searching for an arbitrarily smart and fast evader in a large environment with a team of unmanned aerial vehicles (UAVs) while providing guarantees of detection. Our emphasis is on the fast execution of efficient search strategies that minimize the number of UAVs and the search time. We present the first approach for computing fast search strategies utilizing additional searchers to speed up the execution time and thereby enabling large scale UAV search. In order to scale to very large environments when using UAVs one would either have to overcome the energy limitations of UAVs or pay the cost of utilizing additional UAVs to speed up the search. Our approach is based on coordinating UAVs on sweep lines, covered by the UAV sensors, that move simultaneously through an environment. We present some simulation results that show a significant reduction in execution time when using multiple UAVs and a demonstration of a real system with three ARDrones.},
	keywords = {AR.Drone 2.0, autonomous aerial vehicles, Delays, fast guaranteed search, Multi-robot systems, Robot kinematics, Robot sensing systems, search problem, Search problems, search strategies, sensors, Surveillance, UAV sensors, unmanned aerial vehicles},
	doi = {10.1109/IROS.2013.6697229},
	author = {Kolling, A. and Kleiner, A. and Rudol, P.}
}
@conference {38,
	title = {Fast task-sequence allocation for heterogeneous robot teams with a human in the loop},
	booktitle = {Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems {(IROS)},
	year = {2013},
	abstract = {Efficient task allocation with timing constraints to a team of possibly heterogeneous robots is a challenging problem with application, e.g., in search and rescue. In this paper a mixed-integer linear programming (MILP) approach is proposed for assigning heterogeneous robot teams to the simultaneous completion of sequences of tasks with specific requirements such as completion deadlines. For this purpose our approach efficiently combines the strength of state of the art Mixed Integer Linear Programming (MILP) solvers with human expertise in mission scheduling. We experimentally show that simple and intuitive inputs by a human user have substantial impact on both computation time and quality of the solution. The presented approach can in principle be applied to quite general missions for robot teams with human supervision.},
	keywords = {computation time, Computational modeling, fast task sequence allocation, heterogeneous robot teams, heterogeneous robots, human in the loop, human supervision, human user, integer programming, linear programming, Mathematical model, MILP solvers, mission scheduling, mixed integer linear programming, Multi-robot systems, Resource management, Robot kinematics, Schedules, task allocation},
	doi = {10.1109/IROS.2013.6696570},
	author = {Petersen, K. and Kleiner, A. and Von Stryk, O.}
}
@conference {44,
	title = {Guaranteed search with large teams of unmanned aerial vehicles},
	booktitle = {Proc. of the {IEEE} Int. Conf. on Robotics and Automation (ICRA)},
	year = {2013},
	address = {Karlsruhe, Germany},
	abstract = {We consider the problem of detecting moving and evading targets by a team of coordinated unmanned aerial vehicles (UAVs) in large and complex 2D and 2.5D environments. Our approach is based on the coordination of 2D sweep lines that move through the environment to clear it from all contamination, representing the possibility of a target being located in an area, and thereby detecting all targets. The trajectories of the UAVs are implicitly given by the motion of these sweep lines and their costs are determined by the number of UAVs needed. A novel algorithm that computes low cost coordination strategies of the UAV sweep lines in simply connected polygonal environments is presented. The resulting strategies are then converted to strategies clearing multiply connected and 2.5D environments. Experiments on real and artificial elevation maps with complex visibility constraints are presented and demonstrate the feasibility and scalability of the approach. The algorithms used for the experiments are made available on a public repository.},
	keywords = {2D environment, 2D sweep lines, autonomous aerial vehicles, collision avoidance, Contamination, coordinated unmanned aerial vehicle team, guaranteed search, helicopters, low cost coordination strategies, Multi-robot systems, multiply-connected 2.5D environment, public repository, quadrotors, robot operating system, Robot sensing systems, ROS framework, Search problems, Shape, simply-connected polygonal environment, sweep line motion, Trajectory, trajectory computing, trajectory control, UAV trajectory, unmanned aerial vehicles},
	doi = {10.1109/ICRA.2013.6630990},
	author = {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.}
}
@conference {46,
	title = {The SHERPA project: smart collaboration between humans and ground-aerial robots for improving rescuing activities in alpine environments},
	booktitle = {Proc. of the IEEE Int. Workshop on Safety, Security and Rescue Robotics (SSRR)},
	year = {2012},
	address = {College Station, US},
	abstract = {The goal of the paper is to present the foreseen research activity of the European project {\textquoteleft}{\textquoteleft}SHERPA{\textquoteright}{\textquoteright} whose activities will start officially on February 1th 2013. The goal of SHERPA is to develop a mixed ground and aerial robotic platform to support search and rescue activities in a real-world hostile environment, like the alpine scenario that is specifically targeted in the project. Looking into the technological platform and the alpine rescuing scenario, we plan to address a number of research topics about cognition and control. What makes the project potentially very rich from a scientific viewpoint is the heterogeneity and the capabilities to be owned by the different actors of the SHERPA system: the human rescuer is the {\textquoteleft}{\textquoteleft}busy genius{\textquoteright}{\textquoteright}, working in team with the ground vehicle, as the {\textquoteleft}{\textquoteleft}intelligent donkey{\textquoteright}{\textquoteright}, and with the aerial platforms, i.e. the {\textquoteleft}{\textquoteleft}trained wasps{\textquoteright}{\textquoteright} and {\textquoteleft}{\textquoteleft}patrolling hawks{\textquoteright}{\textquoteright}. Indeed, the research activity focuses on how the {\textquoteleft}{\textquoteleft}busy genius{\textquoteright}{\textquoteright} and the {\textquoteleft}{\textquoteleft}SHERPA animals{\textquoteright}{\textquoteright} interact and collaborate with each other, with their own features and capabilities, toward the achievement of a common goal.},
	keywords = {alpine environments, autonomous aerial vehicles, busy genius, Cognitive Systems, European project, Ground and Aerial Robotics, ground-aerial robots, human rescuer, intelligent donkey, patrolling hawks, real-world hostile environment, rescuing activities, Robust Control, Search and Rescue, search and rescue activities, SHERPA project, smart collaboration, telerobotics, trained wasps},
	doi = {10.1109/SSRR.2012.6523905},
	author = {Marconi, L. and Melchiorri, C. and Beetz, M. and Pangercic, D. and Siegwart, R. and Leutenegger, S. and Carloni, R. and Stramigioli, S. and Bruyninckx, H. and Doherty, P. and Kleiner, A. and Lippiello, V. and Finzi, A. and Siciliano, B. and Sala, A. and Tomatis, N.}
}
@conference {49,
	title = {A Mechanism for Dynamic Ride Sharing based on Parallel Auctions},
	booktitle = {Proc. of the 22th International Joint Conference on Artificial Intelligence (IJCAI)},
	year = {2011},
	address = {Barcelona, Spain},
	abstract = {Car pollution is one of the major causes of green- house emissions, and traffic congestion is rapidly becoming a social plague. Dynamic Ride Sharing (DRS) systems have the potential to mitigate this problem by computing plans for car drivers, e.g. commuters, allowing them to share their rides. Ex- isting efforts in DRS are suffering from the problem that participants are abandoning the system after repeatedly failing to get a shared ride. In this paper we present an incentive compatible DRS solution based on auctions. While existing DRS systems are mainly focusing on fixed assignments that minimize the totally travelled distance, the presented approach is adaptive to individual preferences of the participants. Furthermore, our system allows to tradeoff the minimization of Vehicle Kilometers Travelled (VKT) with the overall probability of successful ride-shares, which is an important feature when bootstrapping the system. To the best of our knowledge, we are the first to present a DRS solution based on auctions using a sealed-bid second price scheme.},
	isbn = {978-1-57735-516-8},
	author = {Kleiner, A. and Nebel, B. and Ziparo, V.}
}
