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