Visual servoing in the task-function framework: A contour following task

We describe an approach to contour following unknown objects using a handeye robotic system. Relevant and sufficient feature points providing optical flow data are extracted from the edges of the target object. The desired motion of the end-effector is computed with the objective of keeping the visual features always at the same target location in the image plane. A cartesian PD controller is used to perform the desired motion by the robot's end-effector. To address thecontrol issues, we take advantage of the unifying robot control theory stated in the literature as thetask-function approach [21]. To validate our approach, we restricted our experiments to motionless objects positioned in a plane parallel to the image plane: three degrees of freedom (two of translation, one of rotation) are thus controlled.

[1]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Nikolaos Papanikolopoulos,et al.  Hand-eye Robotic Visual Servoing Around Moving Objects Using Active Deformable Models , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Takeo Kanade,et al.  Real-time implementation and evaluation of the computed-torque scheme , 1989, IEEE Trans. Robotics Autom..

[4]  Claude Samson,et al.  Application of the Task-function Approach to Sensor-based Control of Robot Manipulators , 1990 .

[5]  Lee E. Weiss,et al.  Dynamic sensor-based control of robots with visual feedback , 1987, IEEE Journal on Robotics and Automation.

[6]  Patrick Rives,et al.  Closed-loop recursive estimation of 3D features for a mobile vision system , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[7]  Frédéric Boussinot,et al.  The ESTEREL language , 1991, Proc. IEEE.

[8]  Pradeep K. Khosla,et al.  Implementing real-time robotic systems using CHIMERA II , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[9]  Rachid Deriche,et al.  Accurate corner detection: an analytical study , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[10]  Claude Samson,et al.  Robot Control: The Task Function Approach , 1991 .

[11]  Daniel Simon,et al.  ORCCAD : towards an open robot controller computer aided design system , 1991 .

[12]  B. Anderson,et al.  Optimal control: linear quadratic methods , 1990 .

[13]  Takeo Kanade,et al.  Vision and control techniques for robotic visual tracking , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[14]  C. S. George Lee,et al.  Adaptive image feature prediction and control for visual tracking with a hand-eye coordinated camera , 1990, IEEE Trans. Syst. Man Cybern..

[15]  Lee E. Weiss,et al.  Dynamic visual servo control of robots: An adaptive image-based approach , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[16]  Z. Zenn Bien,et al.  Feature-based visual servoing of an eye-in-hand robot with improved tracking performance , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[17]  Takeo Kanade,et al.  Experimental Evaluation of Nonlinear Feedback and Feedforward Control Schemes for Manipulators , 1988, Int. J. Robotics Res..

[18]  Eve Coste-Maniere,et al.  Contribution of visual servoing techniques to robotics deburring , 1993, Other Conferences.

[19]  P. K. Khosla,et al.  Adaptive Robotic Visual Tracking , 1991, 1991 American Control Conference.

[20]  B. Espiau,et al.  Reactive objects in a task level open controller , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[21]  Patrick Rives,et al.  A new approach to visual servoing in robotics , 1992, IEEE Trans. Robotics Autom..