Conference Proceeding

# State-space search for improved autonomous UAVs assignment algorithm

Air Vehicles Directorate, Air Force Res. Lab., Wright-Patterson AFB, OH, USA

Proceedings of the IEEE Conference on Decision and Control 01/2005; 3:2911 - 2916 Vol.3. DOI:10.1109/CDC.2004.1428908 ISBN: 0-7803-8682-5 In proceeding of: Decision and Control, 2004. CDC. 43rd IEEE Conference on, Volume: 3 Source: IEEE Xplore

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**ABSTRACT:**Unmanned aerial vehicles (UAVs) need multiple operators as of today. Because of limitations of human attention and sensory cueing the operators cannot use all of the data coming in through these sensors. Large scale autonomy would mean the following: fewer operators, larger areas of coverage, and more vehicles. Rigorous optimization of decision theory based approaches to handling this problem suffer from speed limits to real-time computations. Soft-computing methods based on heuristics (AI, reasoning, neural networks and fuzzy logic) are able to handle certain circumstances but cannot supply any guarantees of performance in unstructured environments. We provide solutions based on rigorous approaches, but avoid heavy real-time computation through off line processing. For mapped regions, we convert maps into traversability graphs using trapezoidal map/voronoi type algorithms. We then find the shortest permissible paths for different vehicles using Dijkstra's algorithm and then preening the allowable paths using constraints on individual vehicles. Out third step consists in determining the minimum time taken by a given vehicle over those paths. We insert margins of safety at each level of this hierarchy: buffer zones (size of buffer zone is a ten meters extended polygon around each building) around mapped structures to account for map errors; buffer zones around flight paths to account for position uncertainty of vehicles; performing 1-D optimal control within limits of the vehicles performance so that vehicles can slow down or speed up in response to unexpected events.01/2011; - [show abstract] [hide abstract]

**ABSTRACT:**We address the problem of dynamically switching the topology of a formation of a number of undistinguishable agents. Given the current and the final topologies, each with n agents, there are n! possible allocations between the initial and final positions of the agents. Given the agents maximum velocities, there is still a degree of freedom in the trajectories that might be used in order to avoid collisions. We seek an allocation and corresponding agent trajectories minimizing the maximum time required by all agents to reach the final topology, avoiding collisions. Collision avoidance is guaranteed through an appropriate choice of trajectories, which might have consequences in the choice of an optimal permutation. We propose here a dynamic programming approach to optimally solve problems of small dimension. We report computational results for problems involving formations with up to 12 agents.11/2010: pages 305-321; -
##### Article: Optimal formation switching

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**ABSTRACT:**We propose a dynamic programming approach to address the problem of determining how a structured formation of autonomous undistinguishable agents can be reorganized into another, eventually non-rigid, formation based on changes in the environment, perhaps unforeseeable. The methodology can also be used to correctly position the agents into a particular formation from an initial set of random locations. Given the information of the current agents location and the final locations, there are n! possible permutations for the n agents, and we seek the one that minimizes a total relative measure, e.g. distance traveled by the agents during the switching. Possible applications can be found amongst surveillance, damage assessment, chemical or biological monitoring, among others, where the switching to another formation, not necessarily predefined, may be required due to changes in the environment.01/2008;

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