This paper develops a method of assignment and path allocation that incorporates a priori collision avoidance and operator workload reduction in assigning multiple tasks to cooperative unmanned aerial vehicles (UAV). The problem is posed as a combinatorial optimization problem. A branch and bound tree search algorithm is implemented for a satisfying solution using a cost function that integrates distance traveled, proximity to other UAVs, and target visitation times. The results demonstrate that the assigned path is near optimal with respect to distance traveled, significantly increases the expected proximity distance to other UAVs, and significantly increases the difference between visitation times of targets. The algorithm runs in less than a tenth of a second allowing on the fly replanning.
Combining Collision Avoidance and Operator Workload Reduction with Cooperative Task Assignment and Path Planning (Preprint)
2006
9 pages
Report
Keine Angabe
Englisch
Aircraft , Operations Research , Computers, Control & Information Theory , Autonomous navigation , Drones , Collision avoidance , Symposia , Robotics , Combinatorial analysis , Adaptive control systems , Uav(Unmanned aerial vehicle) , Branch and bound tree search algorithms , Mav(Micro aerial vehicle) , Counter(Cooperative operations in urban terrain research program) , Cooperative control environments
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