摘要
Drone also known as unmanned aerial vehicle(UAV)has drawn lots of attention in recent years.Quadcopter as one of the most popular drones has great potential in both industrial and academic fields.Quadcopter drones are capable of taking off vertically and flying towards any direction.Traditional researches of drones mainly focus on their mechanical structures and movement control.The aircraft movement is usually controlled by a remote controller manually or the trajectory is pre-programmed with specific algorithms.Consumer drones typically use mobile device together with remote controllers to realize flight control and video transmission.Implementing different functions on mobile devices can result in different behaviors of drones indirectly.With the development of deep learning in computer vision field,commercial drones equipped with camera can be much more intelligent and even realize autonomous flight.In the past,running deep learning based algorithms on mobile devices is highly computational intensive and time consuming.This paper utilizes a novel real-time object detection method and deploys the deep learning model on the modern mobile device to realize autonomous object detection and object tracking of drones.
基金
This work is supported by the National Key R&D Program of China under grant 2018YFB1003205
by the National Natural Science Foundation of China under grant U1836208,U1536206,U1836110,61602253,61672294
by the Jiangsu Basic Research Programs-Natural Science Foundation under grant numbers BK20181407
by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund
by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China。
