Hefei University of Technology

Moning Zhu

Xiaoxuan Hu

Huawei Ma

Guoqiang Wang

Peng Jin

He Luo

Wei Xia

Shanlin Yang

Peng Zhang

Xiaoduo Li

Xiang Fang

Ju Wang

Zhengzheng Liang

Yanqiu Niu

The embodiments of the present disclosure provide a method and system for patrolling an expressway by unmanned aerial vehicles (UAVs). The method is applied to the system including a control center, a plurality of UAVs and a plurality of advertising board charging base stations. The method firstly receives unmanned aerial vehicle (UAV) status information sent by the plurality of unmanned aerial vehicles and road section patrolling data through the control center, and receives advertising board charging base station information sent by the plurality of advertising board charging base stations, then classifies, stores and analyzes the received data and information, and finally generates and sends control commands for the UAVs and charging advertising boards. On one hand, the technical solutions of the present disclosure may comprehensively schedule an UAV formation, may also comprehensively control the advertising board charging base stations, and may further dispose and schedule task responses; and on the other hand, the technical solutions of the present disclosure may analyze situations of accidents, violations and the like and scheduling and usage of the UAVs and the advertising board charging base stations, thereby providing decision support data for the control center.

Method and system for patrolling an expressway by unmanned aerial vehicles

The embodiments of the present invention disclose a method and apparatus for joint optimization of multi-UAV task assignment and path planning. The method comprises: obtaining the location information of a plurality of UAVs and a plurality of target points, the dispersion of groundspeed course angle, and motion parameters of each UAV and wind field; constructing an initial population based on the location information, the dispersion of groundspeed course angle and a preset genetic algorithm; determining the flight status of each UAV and the flight time taken by each UAV to complete a path segment of the corresponding Dubins flight path based on the initial population and the motion parameters, obtaining the total time taken by all the UAVs corresponding to each chromosome to complete the task based on the flight time of the path segment; and subjecting the chromosomes in the initial population to crossover and mutation based on the genetic algorithm and, when a predetermined number of iterations is reached, selecting the optimal Dubins flight path as the joint optimization result. In the embodiments of the present invention, the UAV flight path planning problem is combined with the actual flight environment of the UAV, so that the optimal flight path obtained is superior to the solution in which the UAV speed is constant.

Method and apparatus for joint optimization of multi-UAV task assignment and path planning

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Anhui, China

Moning Zhu