An Eye-To-Hand Panoramic Vision System for 3D Positioning of a Robotic Arm
Chaiyapol Kulpate*, Mehran Mehrandezh**, and Raman Paranjape*
*Electronic Systems Engineering, University of Regina, Regina, Saskatchewan, Canada
**Industrial Systems Engineering, University of Regina, Regina, Saskatchewan, Canada
A novel visual servoing structure is presented for robot positioning under an eye-to-hand camera configuration using panoramic vision. The proposed algorithm is based upon Image-Based Visual Servoing (IBVS) and uses only one fixed camera in conjunction with a stationary flat mirror. A single landmark mounted on the robot’s end-effector along with its mirror reflection provide enough information for 3D reasoning based on a 2D image when viewed by a camera. The equations describing the relationship between the velocity of the coordinate frame attached to the robot’s end-effector and rate of change in image features called the image Jacobian are presented. A novel set of image features that yield a full-rank image Jacobian is introduced. The Visual servoing based on an online estimation of the image Jacobian using a Kalman Filter (KF) is also presented. Simulated and experimental results illustrate the robustness of the proposed visual servoing structure. In addition, the accuracy of the proposed visual servoing structure is evaluated with an error analysis and sensitivity tests.
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