Title :
Dynamic network refinement in automated aircraft route planning
Author :
Hennebry, Michael ; Jian, Kuodi ; Nygard, Kendall E.
Author_Institution :
North Dakota State Univ., Frago
Abstract :
We describe a routing procedure for unmanned aircraft called dynamic resolution refinement (DRR). This new procedure is based on a variation of the A* search algorithm and uses space tessellations. We call this variation search procedure A*´. The routing problem of interest concerns path planning for an unmanned air vehicle (UAV). The benefit of DRR is that it successively improves the accuracy of the path calculation, and also allows a planner to dynamically choose among multiple near optimal routes. This capability reduces the risk of an aircraft being shot down. Since the DRR starts with coarse resolution, the setup time is short, which is important in mission critical applications. The DRR finds a near optimal solution quickly and works well in a resource bound environment. In such an environment, a uniform fine resolution approach would either take too long to find a solution or find a poor solution.
Keywords :
aerospace computing; aircraft control; control engineering computing; integer programming; linear programming; multi-agent systems; remotely operated vehicles; search problems; A* variation search algorithm; automated aircraft route planning; dynamic network resolution refinement; integer linear programming; intelligent agent; space tessellation; unmanned air vehicle; Airborne radar; Aircraft; Artificial intelligence; Fuels; Mission critical systems; Path planning; Routing; Unmanned aerial vehicles; Vehicle dynamics; Weapons; Algorithms; Artificial Intelligence; Intelligent Agent;
Conference_Titel :
Electro/Information Technology, 2007 IEEE International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-0941-9
Electronic_ISBN :
978-1-4244-0941-9
DOI :
10.1109/EIT.2007.4374507