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

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Abstract

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.

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Acknowledgements

This material is based upon work supported, in part, by the National Science Foundation, Partnership for Innovation Program, Grant No. 1430328. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Design, Automation, Robotics and Control (DARC) Lab, University of Utah Robotics Center, Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA

    Dejun Guo, Joseph R. Bourne & Kam K. Leang

  2. The Key Laboratory of System Control and Information Processing, Department of Automation, Shanghai Jiao Tong University, Shanghai, China

    Hesheng Wang

  3. Intelligent Structures and Control Laboratory, Department of Mechanical Engineering, University of Nevada - Las Vegas, Las Vegas, NV, USA

    Woosoon Yim

Authors
  1. Dejun Guo
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  2. Joseph R. Bourne
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  3. Hesheng Wang
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  4. Woosoon Yim
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  5. Kam K. Leang
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Correspondence to Kam K. Leang.

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Communicated by Maurizio Porfiri.

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Guo, D., Bourne, J.R., Wang, H. et al. Adaptive-Repetitive Visual-Servo Control of Low-Flying Aerial Robots via Uncalibrated High-Flying Cameras. J Nonlinear Sci 27, 1235–1256 (2017). https://doi.org/10.1007/s00332-017-9377-2

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  • DOI: https://doi.org/10.1007/s00332-017-9377-2

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