Real-time path planning method for unmanned aerial vehicle based on deep reinforcement learning

Abstract

The invention discloses a real-time path planning method for an unmanned aerial vehicle based on deep reinforcement learning. The method comprises the steps of S1, obtaining the current environment state of the unmanned aerial vehicle from a simulation environment, calculating the threat degree of a target object defense unit to the unmanned aerial vehicle according to a situation evaluation model, and constructing a situation map of a task area of the unmanned aerial vehicle; constructing a main network and a target network of the convolutional neural network and the competitive neural network to perform action selection; S2, obtaining the current environment state of the unmanned aerial vehicle according to the communication link, calculating a threat value of the target object defense unit to the unmanned aerial vehicle according to the situation evaluation model, constructing a situation map of the task areas of the unmanned aerial vehicle, constructing a competitive dual-Q network, loading the trained network model, evaluating the Q value of each action in the current state, selecting the action corresponding to the maximum Q value, determining the flight direction of the unmanned aerial vehicle, and completing the flight task. According to the invention, the autonomous decision-making ability of the unmanned aerial vehicle can be effectively improved, and the method has high robustness and application value.

Description

technical field [0001] The invention mainly relates to the technical field of unmanned aerial vehicles, in particular to a real-time path planning method for unmanned aerial vehicles based on deep reinforcement learning. Background technique [0002] With the continuous development of UAV system technology, UAV (Unmanned Aerial Vehicle, UAV) has been widely used in various military operations and civilian tasks such as industrial inspection, disaster search and rescue, geographic mapping, border patrol, military reconnaissance, etc. . Considering various influencing factors comprehensively, such as UAV range, target location, external threats, etc., planning the optimal path for UAV plays an important role in ensuring the successful completion of the flight mission. Therefore, UAV path planning is the basic and key technology necessary for UAVs to perform various military or civilian tasks. Although UAVs have made great progress in operational autonomy in recent years, it ...

AI Technical Summary

Problems solved by technology

The above methods have their own advantages under specific conditions, but they all need to establish an environment or platform model in advance. When the environment information cannot be obtained in advance or the problem model is too complex, the above algorithms are often not applicable

Images