Details
Original language | English |
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Title of host publication | Proc. of the Int. Conference on Mechatronics and Robotics 2004, MechRob2004 |
Place of Publication | Aachen, Deutschland |
Pages | 436-441 |
Number of pages | 6 |
Publication status | Published - 2004 |
Abstract
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Proc. of the Int. Conference on Mechatronics and Robotics 2004, MechRob2004. Aachen, Deutschland, 2004. p. 436-441.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Using Model-Based Feature Extraction for Uncalibrated Visual Guided Grasping
AU - Hornung, Oliver
AU - Heimann, Bodo
PY - 2004
Y1 - 2004
N2 - In this paper an approach to the feature correspondence problem for image based visual servoing systems is presented. Using an object model calculated off-line, robust image features of a partial scene reconstruction are extracted for tracking by model registration. The registration between model and reconstruction is processed in two stages. The first stage copes with the problem of coarse structural alignment while in the second stage an alternation between reconstruction scale optimization and point registration is adopted for finetuning. As a consequence the reconstruction does not have to be calculated by calibrated cameras which makes the approach suitable for systems with only uncertain intrinsic and extrinsic camera parameters. Experimental results verify the effectiveness of the approach applied to a grasping task with an uncalibrated zoom camera and a 7 DOF uncalibrated manipulator in an eye-in-hand configuration.
AB - In this paper an approach to the feature correspondence problem for image based visual servoing systems is presented. Using an object model calculated off-line, robust image features of a partial scene reconstruction are extracted for tracking by model registration. The registration between model and reconstruction is processed in two stages. The first stage copes with the problem of coarse structural alignment while in the second stage an alternation between reconstruction scale optimization and point registration is adopted for finetuning. As a consequence the reconstruction does not have to be calculated by calibrated cameras which makes the approach suitable for systems with only uncertain intrinsic and extrinsic camera parameters. Experimental results verify the effectiveness of the approach applied to a grasping task with an uncalibrated zoom camera and a 7 DOF uncalibrated manipulator in an eye-in-hand configuration.
M3 - Conference contribution
SP - 436
EP - 441
BT - Proc. of the Int. Conference on Mechatronics and Robotics 2004, MechRob2004
CY - Aachen, Deutschland
ER -