基于智能算法的无人机航迹规划

doi:10.16180/j.cnki.issn1007-7820.2019.02.003

Abstract

Abstract:

This paper proposed a new method for UAV route planning based on K-means algorithm and Hop-field neural network algorithm, which dealt with the formation of multi UAVs under complex constraints and high coverage cruise. A digital map model of the task area was established for the no-fly zone, the target zone and the valid zone required by the mission and the model decomposition was performed to reasonably decompose the effective area into multiple sub-target points. Then the K-means algorithm was used to cluster the target points of UAV cruise, and the Hop-field neural network algorithm was used to carry out UAV trajectory planning for similar sub-target points. Taking the real data of UAV in earthquake relief as an example, the coverage ratio of 90% of the cruise area was simulated, which proved the robustness and effectiveness of the proposed method.

Key words: UAV, formation teamwork, path planning, model area decomposition technique, K means algorithm, Hop field neural network algorithm, coverage ratio

CLC Number:

TP29

YUE Xiu,ZHANG Wei. UAV Path Planning Based on Intelligent Algorithm[J].Electronic Science and Technology, 2019, 32(2): 9-13.

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References 17

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UAV Path Planning Based on Intelligent Algorithm

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