4.6 Article

Adaptive Image-Based Trajectory Tracking Control of Wheeled Mobile Robots With an Uncalibrated Fixed Camera

Journal

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 23, Issue 6, Pages 2266-2282

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2015.2411627

Keywords

Adaptive control; depth-independent image Jacobian matrix; fixed camera; image-based trajectory tracking; wheeled mobile robot

Funding

  1. Shanghai Post-Doctoral Science Foundation [12R21414200]
  2. Special Financial Grant through the China Post-Doctoral Science Foundation [2013T60448]
  3. Shanghai Rising-Star Program [14QA1402500]
  4. China Post-Doctoral Science Foundation [2012M511095]
  5. Natural Science Foundation of China [61105095, 61203361, 61473191]
  6. China Domestic Research Project through the International Thermonuclear Experimental Reactor [2012GB102001, 2012GB102008]

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In this paper, the uncalibrated image-based trajectory tracking control problem of wheeled mobile robots will be studied. The motion of the wheeled mobile robot can be observed using an uncalibrated fixed camera on the ceiling. Different from traditional vision-based control strategies of wheeled mobile robots in the fixed camera configuration, the camera image plane is not required to be parallel to the motion plane of the wheeled mobile robots and the camera can be placed at a general position. To guarantee that the wheeled mobile robot can efficiently track its desired trajectory, which is specified by the desired image trajectory of a feature point at the forward axis of the wheeled mobile robot, we will propose a new adaptive image-based trajectory tracking control approach without the exact knowledge of the camera intrinsic and extrinsic parameters and the position parameter of the feature point. To eliminate the nonlinear dependence on the unknown parameters from the closed-loop system, a depth-independent image Jacobian matrix framework for the wheeled mobile robots will be developed such that unknown parameters in the closed-loop system can be linearly parameterized. In this way, adaptive laws can be designed to estimate the unknown parameters online, and the depth information of the feature point can be allowed to be time varying in this case. The Lyapunov stability analysis will also be performed to show asymptotical convergence of image position and velocity tracking errors of the wheeled mobile robot. The simulation results based on a two-wheeled mobile robot will be given in this paper to illustrate the performance of the proposed approach as well. The experimental results based on a real wheeled mobile robot will also be provided to validate the proposed approach.

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