Uncalibrated Visual Servo control with multi-constraint satisfaction

This paper devises a new multicriteria image-based controller for the control of six degrees of freedom (PUMA560) robotic arm, based upon Linear Matrix Inequality (LMI). The aim lies in developing such a method that neither involves camera calibration parameters nor inverse kinematics. The approach adopted in this paper includes transpose Jacobian control; thus, inverse of the Jacobian matrix is no longer required. The proposed controller allows stabilizing the camera despite the unknown value of the target point depth. To make sure that the features remain in the camera field of view, and to restrict the controller's input using some bounds, visibility and kinematic constraints are introduced in the form of LMIs. By invoking the Lyapunov's direct method, closed-loop stability of the system is ensured. Simulation results are shown for three different cases, which exhibit the system stability and convergence even in the presence of large errors, and present the comparative analysis of both i.e., systems with and without visibility and kinematic constraints.

[1]  François Chaumette,et al.  Potential problems of stability and convergence in image-based and position-based visual servoing , 1997 .

[2]  Oussama Khatib,et al.  The explicit dynamic model and inertial parameters of the PUMA 560 arm , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[3]  M. Spong,et al.  Robot Modeling and Control , 2005 .

[4]  François Chaumette,et al.  Model-free optimal trajectories in the image space: application to robot vision control , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[5]  Sophie Tarbouriech,et al.  Image-based Visual Servo Control Design with Multi-Constraint Satisfaction , 2010 .

[6]  François Chaumette,et al.  Optimal Camera Trajectory with Image-Based Control , 2003, Int. J. Robotics Res..

[7]  Ezio Malis Visual servoing invariant to changes in camera-intrinsic parameters , 2001, IEEE Transactions on Robotics and Automation.

[8]  Francois Chaumette,et al.  Potential problems of unstability and divergence in image-based and position-based visual servoing , 1999, 1999 European Control Conference (ECC).

[9]  Naeem Iqbal,et al.  Uncalibrated eye-in-hand visual servoing: an LMI approach , 2011, Ind. Robot.

[10]  Daniel E. Koditschek,et al.  Visual servoing via navigation functions , 2002, IEEE Trans. Robotics Autom..

[11]  Graziano Chesi,et al.  Camera Displacement via Constrained Minimization of the Algebraic Error , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  James P. Ostrowski,et al.  Visual motion planning for mobile robots , 2002, IEEE Trans. Robotics Autom..

[13]  Graziano Chesi,et al.  Visual Servoing Path Planning via Homogeneous Forms and LMI Optimizations , 2009, IEEE Transactions on Robotics.

[14]  Cordelia Schmid,et al.  Scale & Affine Invariant Interest Point Detectors , 2004, International Journal of Computer Vision.

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

[16]  François Chaumette,et al.  Path planning for robust image-based control , 2002, IEEE Trans. Robotics Autom..