Name
Abstract | ||
|---|---|---|
In this paper, the visual servoing problem is addressed by coupling nonlinear control theory with a convenient representation of the visual information used by the robot. The visual representation, which is based on a linear camera model, is extremely compact to comply with active vision requirements. The devised control law is proven to ensure global asymptotic stability in the Lyapunov sense, assuming exact model and state measurements. It is also shown that, in the presence of bounded uncertainties, the closed-loop behavior is characterized by a global attractor. The well known pose ambiguity arising from the use of linear camera models is solved at the control level by choosing a hybrid visual state vector including both image space (2D) information and 3D object parameters. A method is expounded for on-line visual state estimation that avoids camera calibration. Simulation and real-time experiments validate the theoretical framework in terms of both system convergence and control robustness. (C) 1999 Elsevier Science B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1016/S0921-8890(99)00057-3 | ROBOTICS AND AUTONOMOUS SYSTEMS |
Keywords | Field | DocType |
camera calibration,nonlinear control,active vision,real time,visual servoing | Computer vision,Lyapunov function,State vector,Active vision,Nonlinear control,Computer science,Robustness (computer science),Exponential stability,Camera resectioning,Visual servoing,Artificial intelligence | Journal |
Volume | Issue | ISSN |
29 | 4 | 0921-8890 |
Citations | PageRank | References |
3 | 0.50 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabio Conticelli | 1 | 60 | 7.36 |
| Benedetto Allotta | 2 | 244 | 53.74 |
| Carlo Colombo | 3 | 633 | 52.34 |