Robot Vision SS 2007 Matthias Rüther 1
ROBOT VISION Lesson 9: Robots & Vision
Matthias Rüther
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Contents
Visual Servoing– Principle
– Servoing Types
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Visual Servoing
Vision System operates in a closed control loop.
Better Accuracy than „Look and Move“ systems
Figures from S.Hutchinson: A Tutorial on Visual Servo Control
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Visual Servoing
Example: Maintaining relative Object Position
Figures from P. Wunsch and G. Hirzinger. Real-Time Visual Tracking of 3-D Objects with Dynamic Handling of Occlusion
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Visual Servoing
Camera Configurations:
End-Effector Mounted Fixed
Figures from S.Hutchinson: A Tutorial on Visual Servo Control
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Visual Servoing
Servoing Architectures
Figures from S.Hutchinson: A Tutorial on Visual Servo Control
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Visual Servoing
Position-based and Image Based control
– Position based: • Alignment in target coordinate system• The 3D structure of the target is rconstructed• The end-effector is tracked• Sensitive to calibration errors• Sensitive to reconstruction errors
– Image based:• Alignment in image coordinates• No explicit reconstruction necessary• Insensitive to calibration errors• Only special problems solvable• Depends on initial pose• Depends on selected features
target
End-effector
Image of target
Image of end effector
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Visual Servoing
EOL and ECL control
– EOL: endpoint open-loop; only the target is observed by the camera
– ECL: endpoint closed-loop; target as well as end-effector are observed by the camera
EOL ECL
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Visual Servoing
Position Based Algorithm:1. Estimation of relative pose
2. Computation of error between current pose and target pose
3. Movement of robot
Example: point alignment
p1
p2
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Visual Servoing
Position based point alignment
Goal: bring e to 0 by moving p1
e = |p2m – p1m|
u = k*(p2m – p1m)
pxm is subject to the following measurement errors: sensor position, sensor calibration, sensor measurement error
pxm is independent of the following errors: end effector position, target position
p1m p2m
d
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Visual Servoing Image based point alignment
Goal: bring e to 0 by moving p1
e = |u1m – v1m| + |u2m – v2m|
uxm, vxm is subject only to sensor measurement error
uxm, vxm is independent of the following measurement errors: sensor position, end effector position, sensor calibration, target position
p1 p2
c1 c2
u1
u2
v1 v2
d1d2
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Visual Servoing
Example Laparoscopy
Figures from A.Krupa: Autonomous 3-D Positioning of Surgical Instruments in Robotized Laparoscopic Surgery Using Visual Servoing
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Visual Servoing
Example Laparoscopy
Figures from A.Krupa: Autonomous 3-D Positioning of Surgical Instruments in Robotized Laparoscopic Surgery Using Visual Servoing