1. Chayatat Ratanasawanya Min He April 6, 2010

2.  Recall previous presentation  The goal  Progress report ◦ Image processing ◦ depth estimation ◦ Camera placement  Obstacles ◦ Combine image processing and control Simulink models  Idea for the next step  Questions/Comments

3.  4 visual-servoing structures ◦ Dynamic position-based look-and-move ◦ Dynamic image-based look-and-move ◦ Position-based visual servoing (PBVS) ◦ Image-based visual servoing (IBVS)  Implemented a simulation of the dynamic position-based look-and-move system.  Implemented a Simulink model to locate the centroid of a ping-pong ball in image.

4.  Implement the system using PBVS, IBVS, or both techniques.  Tasks to tackle: ◦ Image processing ◦ Depth estimation ◦ Camera placement on the helicopter model ◦ Combine image processing and control Simulink models. ◦ Jacobian matrix derivation

6.  Use the diameter of the ball in image to estimate the depth Depth, D Focal length F=538 pixel Center of projection Actual ball diameter d b =40mm Ball diameter on image, d img

7. area63494384319923861879149211209851082975103211221075 dm92766456494438363835374039 real dis234.0284.8335.6386.4437.2488538.8589.6 Cal dis234.4282.2335.0386.0436.0487.6565.6601.9561.6608.3577.3542.1552.8

9.  Combining our image processing model and the control model has been a challenging task. Global variable

10. exex eyey Increment in pitch and yaw angles LQR controller

11.  Questions/comments are welcome