Combining force control and visual servoing for planar contour following

The limited bandwidth of sensor-based feedback control restricts the execution speed of a force con- trolled planar contour following task, if the shape and/or pose of the workpiece are unknown. This paper shows how feedforward control of the contour orientation, calculated on-line from an eye-in-hand camera image, results in a faster or more accurately executed task. However, keeping the contour in the camera field of view imposes an additional requirement on the controller which already has to maintain a force controlled contact. This double control problem is specified in the Task Frame formalism and executed in a hybrid position/force control environment. It is solved using the redundancy for rotation in the plane, which exists for rotationally symmetric (tracking) tools. The orientations of task and end effector frames can then be controlled independently. Experimental results are presented to validate the approach.

[1]  Gregory D. Hager Task-Directed Sensor Fusion and Planning: A Computational Approach , 1990 .

[2]  Joris De Schutter,et al.  Specification of force-controlled actions in the "task frame formalism"-a synthesis , 1996, IEEE Trans. Robotics Autom..

[3]  Joris De Schutter,et al.  Model based and sensor based programming of compliant motion tasks , 1993 .

[4]  Friedrich Lange,et al.  Predictive vision based control of high speed industrial robot paths , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[5]  Matthew T. Mason,et al.  Compliance and Force Control for Computer Controlled Manipulators , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  Di Xiao,et al.  Intelligent robotic manipulation with hybrid position/force control in an uncalibrated workspace , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[7]  Ricardo D. Fierro,et al.  The Total Least Squares Problem: Computational Aspects and Analysis (S. Van Huffel and J. Vandewalle) , 1993, SIAM Rev..

[8]  Carlos Canudas de Wit,et al.  Theory of Robot Control , 1996 .

[9]  Jun Shen,et al.  An optimal linear operator for step edge detection , 1992, CVGIP Graph. Model. Image Process..

[10]  Minoru Asada,et al.  Adaptive hybrid control for visual and force servoing in an unknown environment , 1998, IEEE Robotics Autom. Mag..

[11]  Peter I. Corke,et al.  A tutorial on visual servo control , 1996, IEEE Trans. Robotics Autom..

[12]  J. De Schutter,et al.  Combining eye-in-hand visual servoing and force control in robotic tasks using the task frame , 1999, Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480).

[13]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

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

[15]  Hendrik Van Brussel,et al.  Compliant Robot Motion II. A Control Approach Based on External Control Loops , 1988, Int. J. Robotics Res..

[16]  Hendrik Van Brussel,et al.  Compliant Robot Motion I. A Formalism for Specifying Compliant Motion Tasks , 1988, Int. J. Robotics Res..

[17]  Joris De Schutter,et al.  An environment for developing and optimising compliant robot motion tasks , 1993 .

[18]  Pradeep K. Khosla,et al.  Force and vision resolvability for assimilating disparate sensory feedback , 1996, IEEE Trans. Robotics Autom..

[19]  Sabine Van Huffel,et al.  Total least squares problem - computational aspects and analysis , 1991, Frontiers in applied mathematics.