Autonomous Remote Control of Small Unmanned Aircraft

被引:0
|
作者
Ellingson, Jaron [1 ]
Peterson, Cameron [1 ]
机构
[1] Brigham Young Univ, Mech Engn, Provo, UT 84602 USA
来源
关键词
Unmanned Aerial Vehicle; Control Systems; Extended Kalman Filter; Proportional Integral Derivative; Sensors; Aerial Autonomous Logistics; Quadcopter; Artificial Neural Network; Flight Control Surfaces; Small Unmanned Aircraft System; DEEP NEURAL-NETWORKS; TRACKING;
D O I
10.2514/1.I011186
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
In this paper we present a novel approach to controlling small unmanned aircraft in third-person perspective scenarios. Our approach uses monocular imagery to mimic the human ability to perceive and control a remote aircraft. This allows for the autonomous control of a wide variety of aircraft with minimal on-board sensors. We improve upon other 2D single-shot detection methods by estimating a 3D box containing the aircraft, which allows us to capture a vehicle's position and attitude as measurements. Using a constant-jerk Kalman filter, we then estimate the complete aircraft state from these measurements. Finally a proportional-integral-derivative controller is used to provide closed-loop autonomous flight of an aircraft from a remote location. Hardware experiments of a completely autonomous vehicle flying waypoints illustrate the validity of this method.
引用
收藏
页码:369 / 377
页数:9
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