Risk-based discrete multi-path planning method for UAVs in urban environments

HU Xinting; WU Yu

doi:10.7527/S1000-6893.2020.24383

ACTA AERONAUTICAET ASTRONAUTICA SINICA >

2021 , Vol. 42 >Issue 6: 324383 - 324383

DOI: https://doi.org/10.7527/S1000-6893.2020.24383

Electronics and Electrical Engineering and Control

Risk-based discrete multi-path planning method for UAVs in urban environments

HU Xinting ,
WU Yu

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1. School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China;
2. College of Aerospace Engineering, Chongqing University, Chongqing 400044, China

Received date: 2020-06-09

Revised date: 2020-07-27

Online published: 2020-08-21

Supported by

Chongqing Research Program of Basic Research and Frontier Technology (cstc2020jcyj-msxmX0602); Fundamental Research Funds for the Central Universities (2020 CDJ-LHZZ-066)

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Abstract

A risk-based Unmanned Aerial Vehicle (UAV) multi-path planning method is proposed to improve the safety of UAV operations and generate multiple alternative flight paths in discrete urban environments. According to the proposed model of urban environments, flight rules, and principles of safety, a safety analysis model and a multi-path planning model are established respectively. A Clustering Improved Ant Colony Optimization (CIACO) algorithm is employed to enhance algorithm performance on convergence rate and solution quality. In this algorithm, the multi-path planning problem is solved by designing a cluster mechanism and improving original Ant Colony Optimization (ACO) algorithm. Simulation studies show that the proposed method can generate multiple flight paths with low risks at fast convergence rates.

Key words： Unmanned Aerial Vehicle (UAV); urban environments; safety analysis; multi-path planning; Ant Colony Optimization (ACO) algorithm

Cite this article

HU Xinting , WU Yu . Risk-based discrete multi-path planning method for UAVs in urban environments[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021 , 42(6) : 324383 -324383 . DOI: 10.7527/S1000-6893.2020.24383

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