path planning, UAV, unmanned aircraft
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 when there has been no improvement in the path for some number of iterations, resulting in a path planner that provides short-distance paths in short running times.
Original Publication Citation
Jason Howlett, Michael A. Goodrich, and Tim McLain. "Learning Real-Time A* Path Planner for Sensing Closely-Spaced Targets from an Aircraft". AIAA Guidance, Navigation, and Control Conference and Exhibit, (August 14, 2003). DOI: 10.2514/6.2003-5338
BYU ScholarsArchive Citation
Howlett, Jason K.; Goodrich, Michael A.; and McLain, Timothy W., "Learning Real-Time A* Path Planner for Sensing Closely-Spaced Targets from an Aircraft" (2003). Faculty Publications. 1512.
Ira A. Fulton College of Engineering and Technology
Howlett, J., Goodrich, M., and McLain, T. Learning Real-Time A* Path Planner for Sensing Closely-Spaced Targets from an Aircraft, Proceedings of the AIAA Guidance, Navigation, and Control Conference, AIAA-2003-5338, August 2003, Austin, Texas. doi: 10.2514/6.2003-5338
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