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原文传递 Unmanned Aircraft Collision Avoidance Using Partially Observable Markov Decision Processes.

题名：	Unmanned Aircraft Collision Avoidance Using Partially Observable Markov Decision Processes.
作者：	S. Temizer; M. J. Koehenderfer; L. P. Kaelbling; T. Lozano-Perez; J. K. Kuchar;
关键词：	unmanned aircraft,collision avoidance;aviation safety, aircraft, configuration, acceleration, algorithms, automation, sensors, markov process, air transportation, simulation, performance evaluation, air traffic control;civil airspace
摘要：	Before unmanned aircraft can fly safety in civil airspace, robust airborne collision avoidance systems must be developed. Instead of hand-crafting a collision avoidance algorithm for every combination of sensor and aircraft configuration, this project investigates the automatic generation of collision avoidance logic given models of aircraft dynamics, sensor performance, and intruder behavior. By formulating the problem of collision avoidance as a partially-observable Markov decision process (POMDP), a generic POMDP solvent can be used to generate avoidance strategies that optimize a cost function that balances flight-plan deviation with collision. Experimental results demonstrate the suitability of such an approach using three different sensor modalities and two aircraft performance models. / Supplementary Notes: Sponsored by Department of the Air Force, Washington, DC. / Availability Note: Order this product from NTIS by: phone at 1-800-553-NTIS (U.S. customers); (703)605-6000 (other countries); fax at (703)605-6900; and email at orders@ntis.gov. NTIS is located at 5301 Shawnee Road, Alexandria, VA, 22312, USA.
报告类型：	科技报告