Zhang, Kun (Northwestern Polytechnical University), Li, Ke (Northwestern Polytechnical University), He, Jianliang (Science and Technology on Electro-Optic Control Laboratory, Luoy), SHI, Haotian (Northwestern Polytechnical University), Wang, Yongting (Science and Technology on Electro-Optic Control Laboratory), Niu, Chen (Xi’an JiaoTong University)

An UAV Autonomous Maneuver Decision-Making Algorithm for Route Guidance

Scheduled for presentation during the Regular Session "Autonomy I" (WeA1), Wednesday, September 2, 2020, 11:00−11:20, Macedonia Hall

2020 International Conference on Unmanned Aircraft Systems (ICUAS), September 1-4, 2020 (Postponed from June 9-12, 2020), Athens, Greece

This information is tentative and subject to change. Compiled on April 19, 2024

Abstract

In order to improve the autonomy of UAV for route guidance, an UAV autonomous maneuver decision- making algorithm is proposed. The optimal UAV maneuver policy is developed in an interactive environment. Firstly, the UAV maneuver decision-making model based on MDPs was established, where the flight state space, the flight action space and the flight assessment function are designed. Then, we proposed the algorithm based on Double Deep Q-Learning with Prioritized Experience Replay. Finally, according to the simulation results, the efficiency and autonomy of algorithm we proposed is proved.