Robust visual tracking control system of a mobile robot based on a dual-Jacobian visual interaction model

  • Authors:

  • Chi-Yi Tsai;Kai-Tai Song;Xavier Dutoit;Hendrik Van Brussel;Marnix Nuttin

  • Affiliations:

  • Department of Electrical and Control Engineering, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan, ROC;Department of Electrical and Control Engineering, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan, ROC;Department of Mechanical Engineering, Division PMA, K. U. Leuven, Celestijnenlaan 300B, B-3001 Leuven, Belgium;Department of Mechanical Engineering, Division PMA, K. U. Leuven, Celestijnenlaan 300B, B-3001 Leuven, Belgium;Department of Mechanical Engineering, Division PMA, K. U. Leuven, Celestijnenlaan 300B, B-3001 Leuven, Belgium

  • Venue:
  • Robotics and Autonomous Systems
  • Year:
  • 2009

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Abstract

This paper presents a novel design of a robust visual tracking control system, which consists of a visual tracking controller and a visual state estimator. This system facilitates human-robot interaction of a unicycle-modeled mobile robot equipped with a tilt camera. Based on a novel dual-Jacobian visual interaction model, a robust visual tracking controller is proposed to track a dynamic moving target. The proposed controller not only possesses some degree of robustness against the system model uncertainties, but also tracks the target without its 3D velocity information. The visual state estimator aims to estimate the optimal system state and target image velocity, which is used by the visual tracking controller. To achieve this, a self-tuning Kalman filter is proposed to estimate interesting parameters and to overcome the temporary occlusion problem. Furthermore, because the proposed method is fully working in the image space, the computational complexity and the sensor/camera modeling errors can be reduced. Experimental results validate the effectiveness of the proposed method, in terms of tracking performance, system convergence, and robustness.