Title :
Vision-based control invariant to camera intrinsic parameters: stability analysis and path tracking
Author_Institution :
ICARE Project, I.N.R.I.A., Sophia Antipolis, France
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper concerns the stability analysis of a new vision-based control which is invariant to camera intrinsic parameters. The necessary and sufficient conditions for the local asymptotic stability show that the control law is robust in the presence of large calibration errors. Local stability implies that the system can accurately track a path in the invariant space. Even if the camera is uncalibrated, the path can be chosen such that the camera follows a straight line in the Cartesian space. Simple sufficient conditions are given in order to keep the tracking error bounded.
Keywords :
asymptotic stability; control system analysis; robot vision; robust control; tracking; Cartesian space; camera intrinsic parameter invariance; local asymptotic stability; local stability; necessary and sufficient conditions; path tracking; robust control law; stability analysis; vision-based control; Asymptotic stability; Calibration; Cameras; Error correction; Manipulators; Orbital robotics; Robot vision systems; Stability analysis; Sufficient conditions; Visual servoing;
Conference_Titel :
Robotics and Automation, 2002. Proceedings. ICRA '02. IEEE International Conference on
Print_ISBN :
0-7803-7272-7
DOI :
10.1109/ROBOT.2002.1013364