710.088 ROBOT VISION („Messen aus Bildern“) 2VO 1KU Matthias Rüther. Kawada Industries Inc. DLR. Organization. VO : Tuesday 14:15-15:45 Seminarraum ICG Exam: Written Exam Oral Exam if Requested KU:implementation of lecture topics in the real
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Kawada Industries Inc.
VO: Tuesday 14:15-15:45
Exam: Written Exam
Oral Exam if Requested
KU:implementation of lecture topics in the real
world (on the lab-robots)
Groups of three students
Possible problems on the last slide
Scheduling of topics: 8.3.2005
If you are interested: excursions to industrial vision
companies (Alicona Imaging, M&R)
1.3. : Introduction and Overview
8.3. : Projective Geometry (1)
15.3. : Projective Geometry (2)
12.4. : Projective Geometry (3)
19.4. : Projective Geometry (4)
26.4. : Camera Technologies
3.5. :Shape From X (1)
10.5. : Shape From X (2)
24.5. : Shape From X (3)
31.5. : Robot Kinematics (1)
7.6. : Robot Kinematics (2)
14.6. : Tracking of Moving Objects
21.6. : Visual Servoing / Hand Eye Coordination
"A reprogrammable, multifunctional manipulator designed to move material, parts, tools, or specialized devices through various programmed motions for the performance of a variety of tasks"
Robot Institute of America, 1979
… in a three-dimensional environment.
Service and Assistance
[Whitney, D. E., Lozinski, C. A. and Rourke, J. M. (1986) Industrial robot forward calibration method and results.]
Combining Computer Vision and Robotics
Motion Planning: Given a known world and a cooperative mechanism, how do I get there from here ?
Localization: Given sensors and a map, where am I ?
Vision: If my sensors are eyes, what do I do?
Mapping: Given sensors, how do I create a useful map?
Bug Algorithms: Given an unknowable world but a known goal and local sensing, how can I get there from here?
Kinematics: if I move this motor somehow, what happens in other coordinate systems ?
Control (PID): what voltage should I set over time ?
Motor Modeling: what voltage should I set now ?
"Computer Vision describes the automatic deduction of the structure and the properties of a (possible dynamic) three-dimensional world from either a single or multiple two-dimensional images of the world"
[Nalva VS, "A Guided Tour of Computer Vision"]
Figures from PRIP, TU Vienna
The final map:
Figures from P.Wunsch: Registration of CAD-Models to Images by Iterative Inverse Perspective Matching