Abstract
Visual servoing, or the control of motion on the basis of image analysis in a closed loop, is more and more recognized as an important tool in modern robotics. Here, we present a new model-driven approach to derive a description of the motion of a target object. This method can be subdivided into an illumination invariant target detection stage and a servoing process which uses an adaptive Kalman filter to update the model of the non-linear system. This technique can be applied to any pan-tilt zoom camera mounted on a mobile vehicle as well as to a static camera tracking moving environmental features.
Original language | English |
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Pages (from-to) | 225-249 |
Number of pages | 25 |
Journal | Robotics and Autonomous Systems |
Volume | 47 |
Issue number | 4 |
DOIs | |
Publication status | Published - 31 Jul 2004 |
Keywords
- Bayesian modeling
- Color constancy
- Target tracking
- Visual servoing