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Vision Tracking System

Vision Tracking System. Presented By Timothy Bagnull James Deloge Chad Helm Matthew Sked ECSE 4962 – Control Systems Design Rensselaer Polytechnic Institute 4/22/03. Overview. Objective and Specifications System Design Testing and Verification Problems Encountered

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Vision Tracking System

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  1. Vision Tracking System Presented By Timothy Bagnull James Deloge Chad Helm Matthew Sked ECSE 4962 – Control Systems Design Rensselaer Polytechnic Institute 4/22/03

  2. Overview • Objective and Specifications • System Design • Testing and Verification • Problems Encountered • System Demonstration • Conclusions

  3. System CAD Model

  4. Objective and Specifications • Track a moving point with a camera and pan-tilt system. • Controller Specifications • Maximum target speed: 1 ft/s • Settling time: 0.1 s • Overshoot: 2 % • Vision Specifications • Initialize system using an edge detection algorithm • Track target using a Kalman Filter

  5. System Design: Controller • Linear Controller • Effects of Coulomb Friction • Real Time System Response • Motor Saturation

  6. System Design: ControllerLinear Controller - Pan

  7. System Design: Controller Linear Controller - Tilt

  8. Effects of Coulomb Friction

  9. Effects of Coulomb Friction

  10. System Design: ControllerReal Time System Response - Pan

  11. System Design: ControllerReal Time System Response - Tilt

  12. System Design: ControllerMotor Saturation - Pan

  13. System Design: ControllerMotor Saturation - Tilt

  14. System Design: Vision • Implemented using C++ • 4 levels of communication • Camera – Frame Grabber – Computer - ARCS • Find the target: Roberts Edge Detector • Track the target: Incremental Step Function • Future Modification: Kalman Filter, Pattern Recognition

  15. System Design: Vision • Roberts Edge Detector • Calculates the first order image gradient magnitude • Through a threshold function we determine which pixels are line pixels and which are not • By assuming an ideal environment we can calculate the center of the point by taking the mean of our line pixels

  16. System Design: Vision Normal Lighting Conditions Original Screen Grab | Edge Detection Output

  17. System Design: Vision Poor Lighting Conditions Original Screen Grab | Edge Detection Output

  18. System Design: Vision Focus Conditions Original Screen Grab | Edge Detection Output

  19. System Design:Vision • Incremental Step Function • Determines target position in coordinate frame • Steps towards target using increment function (0,0) (640,0) -,- +,- (320,240) +,+ -,+ (480,0) (640,480)

  20. Testing and Verification • Controller • Trajectory program • Line,Circle, Jog Functions • Vision • Edge Detection • Incremental Step Function • System

  21. Problems Encountered • Real time system controller tuning vs. simulated controller tuning • Coordinate transformations between vision and ARCS systems • Learning programming interfaces between mechanical and visual systems

  22. Final Performance Maximum tracking speed: 0.5 ft/s Settling time: 1 s Overshoot: 50% Initial Specifications Maximum target speed: 1 ft/s Settling time: 0.1 s Overshoot: 2 % Final System Performance

  23. Open Loop ResponsePan: Torque at 0.1 Nm

  24. Open Loop ResponseTilt: Torque at 0.09Nm

  25. Conclusion • We successfully implemented a vision system with a mechanical pan/tilt • Future work can be done to make this system much more robust • Overall we have shown that vision can be a used as an effective sensor in controls

  26. Demonstration • Independent joint test • Track horizontally moving target • Track vertically moving target • System test • Random Motion • Tracking performance test

  27. Questions?

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