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Autonomous Vehicle Technologies For Small Fixed Wing Uavs, Derek B. Kingston, Randal Beard, Timothy Mclain, Michael Larsen, Wei Ren
Autonomous Vehicle Technologies For Small Fixed Wing Uavs, Derek B. Kingston, Randal Beard, Timothy Mclain, Michael Larsen, Wei Ren
Faculty Publications
Autonomous unmanned air vehicle flight control systems require robust path generation to account for terrain obstructions, weather, and moving threats such as radar, jammers, and unfriendly aircraft. In this paper, we outline a feasible, hierarchal approach for real-time motion planning of small autonomous fixed-wing UAVs. The approach divides the trajectory generation into four tasks: waypoint path planning, dynamic trajectory smoothing, trajectory tracking, and low-level autopilot compensation. The waypoint path planner determines the vehicle's route without regard for the dynamic constraints of the vehicle. This results in a significant reduction in the path search space, enabling the generation of complicated paths …
Learning Real-Time A* Path Planner For Sensing Closely-Spaced Targets From An Aircraft, Jason K. Howlett, Michael A. Goodrich, Timothy W. Mclain
Learning Real-Time A* Path Planner For Sensing Closely-Spaced Targets From An Aircraft, Jason K. Howlett, Michael A. Goodrich, Timothy W. Mclain
Faculty Publications
This work develops an any-time path planner, based on the learning real-time A* (LRTA*) search, for generating flyable paths that allow an aircraft with a specified sensor footprint to sense a group of closely-spaced targets. The LRTA* algorithm searches a tree of flyable paths for the branch that accomplishes the desired objectives in the shortest distance. The tree of paths is created by assembling primitive turn and straight sections of a specified step size. The operating parameters for the LRTA* search directly influence the running time and path-length performance of the search. A modified LRTA* search is presented that terminates …