Path Planning of Unmanned Aerial Vehicle in Complex Environments Based on State-Detection Twin Delayed Deep Deterministic Policy Gradient

Path Planning of Unmanned Aerial Vehicle in Complex Environments Based on State-Detection Twin Delayed Deep Deterministic Policy Gradient

This paper investigates the path planning problem of an unmanned aerial vehicle (UAV) for completing a raid mission through ultra-low altitude flight in complex environments. The UAV needs to avoid radar detection areas, low-altitude static obstacles, and low-altitude dynamic obstacles during the fl...

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Bibliographic Details
Main Authors: Danyang Zhang, Zhaolong Xuan, Yang Zhang, Jiangyi Yao, Xi Li, Xiongwei Li
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Machines
Subjects:
unmanned aerial vehicle
deep reinforcement learning
TD3
dynamic reward function
state detection
Online Access:https://www.mdpi.com/2075-1702/11/1/108

Internet

https://www.mdpi.com/2075-1702/11/1/108

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