M. Vincze, M. Ayromlou, S. Chroust, M. Zillich, W. Ponweiser, D. Legenstein:
"Dynamic Aspects of Visual Servoing and a Framework for Real-Time 3D Vision for Robotics";
in: "Lecture Notes in Computer Science Vol. 2238: Sensor Based Intelligent Robots - Selected Revised Papers of the International Workshop Dagstuhl Castle '00",
G. Hager, H. Christensen, H. Bunke, R. Klein (Hrg.);
Vision-based control needs fast and robust tracking. The
conditions for fast tracking are derived from studying the dynamics of
the visual servoing loop. The result indicates how to build the vision system
to obtain high dynamic performance of tracking. Maximum tracking
velocity is obtained when running image acquisition and processing in
parallel and using appropriately sized tracking windows. To achieve the
second criteria, robust tracking, a model-based tracking approach is enhanced
with a method of Edge Projected Integration of Cues (EPIC).
EPIC uses object knowledge to select the correct feature in real-time.
The object pose is calculated from the features at every tracking cycle.
The components of the tracking system have been implemented in a
framework called Vision for Robotics (V4R). V4R has been used within
the EU-funded project RobVision to navigate a robot into a ship section
using the model data from the CAD-design. The experiments show the
performance of tracking in different parts of the ship mock-up.
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