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Adaptive-Repetitive Visual-Servo Control of Low-Flying Aerial Robots via Uncalibrated High-Flying Cameras

机译:通过未校准的高飞行相机的低飞空中机器人的自适应重复视觉伺服控制

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摘要

This paper presents the design and implementation of an adaptive-repetitive visual-servo control system for a moving high-flying vehicle (HFV) with an uncalibrated camera to monitor, track, and precisely control the movements of a low-flying vehicle (LFV) or mobile ground robot. Applications of this control strategy include the use of high-flying unmanned aerial vehicles (UAVs) with computer vision for monitoring, controlling, and coordinating the movements of lower altitude agents in areas, for example, where GPS signals may be unreliable or nonexistent. When deployed, a remote operator of the HFV defines the desired trajectory for the LFV in the HFV's camera frame. Due to the circular motion of the HFV, the resulting motion trajectory of the LFV in the image frame can be periodic in time, thus an adaptive-repetitive control system is exploited for regulation and/or trajectory tracking. The adaptive control law is able to handle uncertainties in the camera's intrinsic and extrinsic parameters. The design and stability analysis of the closed-loop control system is presented, where Lyapunov stability is shown. Simulation and experimental results are presented to demonstrate the effectiveness of the method for controlling the movement of a low-flying quadcopter, demonstrating the capabilities of the visual-servo control system for localization (i.e.,, motion capturing) and trajectory tracking control. In fact, results show that the LFV can be commanded to hover in place as well as track a user-defined flower-shaped closed trajectory, while the HFV and camera system circulates above with constant angular velocity. On average, the proposed adaptive-repetitive visual-servo control system reduces the average RMS tracking error by over 77% in the image plane and over 71% in the world frame compared to using just the adaptive visual-servo control law.
机译:本文介绍了一种用于移动高飞行车(HFV)的自适应重复视觉伺服控制系统的设计和实现,具有未校准的相机来监控,轨道,并精确地控制低飞行车辆(LFV)的运动或移动地机器人。这种控制策略的应用包括使用具有计算机视觉的高飞无人驾驶飞行器(无人机),用于监测,控制和协调区域中的下高度代理的运动,例如,GPS信号可能是不可靠的或不存在的。部署时,HFV的远程操作员定义了HFV的相机帧中LFV的所需轨迹。由于HFV的圆周运动,图像帧中的LFV的所得到的运动轨迹可以在时间周期性地,因此利用自适应重复的控制系统进行调节和/或轨迹跟踪。自适应控制法能够处理相机内在和外在参数中的不确定性。提出了闭环控制系统的设计和稳定性分析,其中显示了Lyapunov稳定性。提出了模拟和实验结果来证明控制低飞Quadcopter的运动的方法的有效性,证明了视觉伺服控制系统的定位(即,运动捕获)和轨迹跟踪控制的能力。事实上,结果表明,可以命令LFV将悬停在适当位置以及轨道上的用户定义的花状闭合轨迹,而HFV和相机系统以恒定的角速度循环。平均而言,与使用自适应视觉伺服控制法相比,所提出的自适应重复的视觉伺服控制系统在图像平面中减少了超过77%的平均RMS跟踪误差,并且在世界帧中超过71%。

著录项

  • 来源
    《Journal of nonlinear science》 |2017年第4期|共22页
  • 作者单位

    Univ Utah Dept Mech Engn Robot Ctr Design Automat Robot &

    Control DARC Lab Salt Lake City UT 84112 USA;

    Univ Utah Dept Mech Engn Robot Ctr Design Automat Robot &

    Control DARC Lab Salt Lake City UT 84112 USA;

    Shanghai Jiao Tong Univ Dept Automat Key Lab Syst Control &

    Informat Proc Shanghai Peoples R China;

    Univ Nevada Las Vegas Dept Mech Engn Intelligent Struct &

    Control Lab Las Vegas NV USA;

    Univ Utah Dept Mech Engn Robot Ctr Design Automat Robot &

    Control DARC Lab Salt Lake City UT 84112 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 数学;
  • 关键词

    Visual-servo control; Adaptive control; Repetitive control; Aerial robots; UAVs;

    机译:视觉伺服控制;自适应控制;重复控制;空中机器人;无人机;

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