1 / 12

Understanding Vision-Based Motion Control for Robots

Learn how to translate visual input into motor actions using geometric transforms and coordinate rotations. Explore robot models, coordinate frames, and transformations with detailed examples in Matlab. Understand the interaction between cameras and robots in closed-loop servoing systems.

ruthedgar
Download Presentation

Understanding Vision-Based Motion Control for Robots

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. Vision Based Motion Control CMPUT 610 2001 Martin Jagersand

  2. How to go from Visual sensationto Motor action? • Camera -> Robot coord Robot -> Object

  3. Closed loop servoing • We focus on the geometric transforms EE

  4. Camera Center of projection Different models Robot Base frame End-effector frame Object Lots of possible coordinates

  5. Coordinate rotation • Example: Around y-axis Z’ P X’ X

  6. Euler angles • Note: Successive rotations. Order matters.

  7. Rotation and translation • Translation t’ in new o’ coordinates Z’ P X’ X

  8. Successive translation and rotation % robocop Simulates a 3 joint robot function Jpos = robocop(theta1,theta2,theta3,L1,L2,L3,P0) Rxy1 = [cos(theta1) sin(theta1) 0 -sin(theta1) cos(theta1) 0 0 0 1]; Rxz2 = [cos(theta2) 0 sin(theta2) 0 1 0 -sin(theta2) 0 cos(theta2)]; Rxz3 = [cos(theta3) 0 sin(theta3) 0 1 0 -sin(theta3) 0 cos(theta3)]; P1 = P0 + Rxy1*[L1 0 0]'; P2 = P1 + Rxy1*Rxz2*[L2 0 0]'; P3 = P2 + Rxy1*Rxz2*Rxz3*[L3 0 0]'; Jpos = [P0 P1 P2 P3]; ExampleMatlab robot

  9. Homogeneous coordinates • Write as matrix multiplications only • 3-vectors -> 4 vectors • Affine -> homogeneous

  10. Denavit-Hartenberg • Particular choice of homogeneous parameterization, see eq. 2.8 in Alexa’s thesis

  11. Perspective Camera • In homogeneous 4-vector • Remove 3rd row for standard camera plane proj

  12. Hand-Eye system Motor-Visual function: y=f(x)

More Related