@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.}
}
