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Vision and Obstacle Avoidance In Cartesian Space

Vision and Obstacle Avoidance In Cartesian Space. Why is Obstacle Avoidance Important. Workspace can change unexpectedly No prior knowledge of workspace Multiple robots in workspace Humans in workspace!. Addressing the Issue. Vision Object Identification Coordinate Transformation

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Vision and Obstacle Avoidance In Cartesian Space

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  1. Vision and Obstacle Avoidance In Cartesian Space

  2. Why is Obstacle Avoidance Important • Workspace can change unexpectedly • No prior knowledge of workspace • Multiple robots in workspace • Humans in workspace!

  3. Addressing the Issue • Vision • Object Identification • Coordinate Transformation • Control • Trajectory generator avoidance • Impedance controllers

  4. Vision Introduction • Cameras • Light sensitive chips • Light • Visible spectrum • Color • Red • Blue • Green

  5. Image acquisition • Grayscale • Bayer • Binary

  6. Common feature extraction techniques • Edge Detection • Edge(image,method) • Sobel • Prewitt • canny • Corner detection • Corner(image) • SIFT • SURF • Color schemed detection • Achieved through logic

  7. Color schemed detection demo • Now that we have the pixel value from our image lets find the Cartesian coordinate of this object.

  8. Camera frame is our target in the camera perspective in the Cartesian. Finding is not easy. Problems with depth

  9. Scaling the x and y coordinate by z we can make an image point Let M Where Pixel point =principal length Principal point Pixel Origin Transforming from 3d to 2d where the mapping is not one-to-one, i.e. unique inverse does not exist because of the depth

  10. Camera Calibration are intrinsic camera properties that can only be determined through camera calibration, since each camera has different properties. is an extrinsic property that will change depending on the orientation of the camera. Best resource for camera calibration is http://www.vision.caltech.edu/bouguetj/calib_doc/ Once the calibration is done the intrinsic properties don’t need to be calculated again.

  11. Obstacle avoidance Vision Vision based controller

  12. Haptic Geometries Using basic geometries find the optimal path around the object and back to the normal trajectory.

  13. Vision Impedance Controller Vision controls the and in Effect changes entire system response and can easily make system unstable. Takes extensive knowledge of controller and system response.

  14. An alternative approach Control Loop A Vision Model Loop

  15. Questions?

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