1 / 13

ROBOT VISION Lesson 9: Robots & Vision Matthias Rüther

ROBOT VISION Lesson 9: Robots & Vision Matthias Rüther. Contents. Visual Servoing Principle Servoing Types. 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.

oke
Download Presentation

ROBOT VISION Lesson 9: Robots & Vision Matthias Rüther

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ROBOT VISIONLesson 9: Robots & VisionMatthias Rüther

  2. Contents • Visual Servoing • Principle • Servoing Types

  3. 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

  4. 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

  5. Visual Servoing • Camera Configurations: End-Effector Mounted Fixed Figures from S.Hutchinson: A Tutorial on Visual Servo Control

  6. Visual Servoing • Servoing Architectures Figures from S.Hutchinson: A Tutorial on Visual Servo Control

  7. 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 End-effector target Image of end effector Image of target

  8. 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

  9. Visual Servoing • Position Based Algorithm: • Estimation of relative pose • Computation of error between current pose and target pose • Movement of robot • Example: point alignment p1 p2

  10. p1m p2m d 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

  11. 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 u1 v1 v2 u2 d1 d2 c1 c2

  12. Visual Servoing • Example Laparoscopy Figures from A.Krupa: Autonomous 3-D Positioning of SurgicalInstruments in Robotized LaparoscopicSurgery Using VisualServoing

  13. Visual Servoing • Example Laparoscopy Figures from A.Krupa: Autonomous 3-D Positioning of SurgicalInstruments in Robotized LaparoscopicSurgery Using VisualServoing

More Related