Robust Vision-Based Pose Control

The problem of controlling the spatial position and orientation of a robotic platform based on the image data obtained from a video camera mounted on that platform is considered. More specifically, we propose control laws that will cause the robot to achieve and maintain a fixed position and orientation with respect to a set of feature points in the scene. We demonstrate analytically that the proposed control scheme is globally convergent even in the presence of large calibration errors in both the intrinsic parameters of the camera and in the extrinsic parameters which relate the frame of reference of the camera to the body frame of the robot platform which is being controlled. Furthermore, no a priori knowledge about the structure of the scene is assumed.

Authors

• Camillo J. Taylor
• Jim Ostrowski 0001

Keywords

• Robust control
• Robot vision systems
• Cameras
• Layout
• Control systems
• Calibration
• Robot control
• Robot sensing systems
• Jacobian matrices
• Robustness
• Control Strategy
• Optimal Control
• Presence Of Errors
• Intrinsic Parameters
• Extrinsic Parameters
• Scene Structure
• Image Features
• Local Features
• Angular Velocity
• Relative Orientation
• Imaging Measurements
• Rotation Axis
• Target Object
• Robotic Arm
• End-effector
• Camera Position
• Robot Manipulator
• Direct Translation
• Camera Frame
• Translation Error
• Translational Velocity
• Rotation Error
• Scene Features
• Visual Servoing
• Fundamental Matrix
• Body Velocity
• Scaling Factor
• Derivative Of Function
• Upper Triangular
• Right-hand Side