Path planning is a key technology for Unmanned Aerial Vehicles (UAVs) to complete the operational mission in a complex battlefield environment. A step-by-step path planning method based on the Layered Double Deep Q-Network with Prioritized Experience Replay (Layered PER-DDQN) is proposed in this paper. The novel method is constructed by combining the threat avoidance network and collision-free network based on the PER-DDQN framework. By analyzing the current environment of the UAV, the networks output threat avoidance action vector and obstacle avoidance action vector, and the method does a weighted summation of the action vectors according to the weight of the subproblems to obtain the final action. The simulation experiment verifies that the Layered PER-DDQN path planning method has better convergence and practicability than the Deep Q-Network and A* algorithm.
A Novel UAV Path Planning Method Based on Layered PER-DDQN
Lect. Notes Electrical Eng.
Asia-Pacific International Symposium on Aerospace Technology ; 2021 ; Korea (Republic of) November 15, 2021 - November 17, 2021
The Proceedings of the 2021 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2021), Volume 2 ; Chapter : 51 ; 693-702
2022-09-30
10 pages
Article/Chapter (Book)
Electronic Resource
English
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