1. May 2008US Sensor Calibration1 Ultrasonic Sensors Calibration Omar A. Daud Truc-Vien T. Nguyen May 16, 2008

2. May 2008 US Sensor Calibration 2 Plan Ultrasonic sensors Calibration Approaches Analysis Conclusion

3. May 2008 US Sensor Calibration 3 Evaluate attributes of a target by interpreting the echoes of sound waves.  Generate high frequency sound waves and evaluate the echo which is received back by the sensor.  Sensors calculate the time interval between sending the signal and receiving the echo to determine the distance to an object. Ultrasonic sensors

4. May 2008 US Sensor Calibration 4 Plan Ultrasonic sensors Calibration Approaches Analysis Conclusion

5. May 2008 US Sensor Calibration 5 In performing a calibration, the following steps are necessary:  Examine the construction of the instrument, identifying the inputs.  Decide which of the inputs are significant for the application.  By holding some inputs constant, varying others, and recording the output(s), develop the desired static input-output relations Calibration

6. May 2008 US Sensor Calibration 6 Plan Ultrasonic sensors Calibration Approaches Analysis Conclusion

7. May 2008 US Sensor Calibration 7 Static Calibration Approach Object Distance [Cm]MeanStd field = 60 [Cm] Sensor 4Sensor 5Sensor 6Sensor 4Sensor 5Sensor 6 Eighth_field18,2412,03914,130,120 Quarter_field41,1319,9217,8521,640,190,33 Half_field42,2233,8731,6922,320,260,33 1_field65,8456,9259,685,923,661,61 2_field59,6347,3160,9818,5825,587,59 3_field56,6749,0955,0921,5624,4912,80 All inputs, except one are kept at some constant values. Then the one input under study is varied over some range of constant values, which causes the output(s) to vary over some range of constant values. Considerable care in choosing the means of determining the numerical values of these inputs.

8. Support Vector Machine (SVM) Approach LibSVM – Polynomial kernel, degree = 3, One vs. One Parameter C = 2; n-fold cross-validation n = 10  12 sensors: accuracy = 58.3667  4 sensors 4,5,6,7: accuracy = 84.5667  3 sensors 4,5,6: accuracy = 85.4333 Correlation between Sensors - Distance

9. May 2008 US Sensor Calibration 9 Plan Ultrasonic sensors Calibration Approaches Analysis Conclusion

10. May 2008 US Sensor Calibration 10 Analysis – Sensor 4

11. May 2008 US Sensor Calibration 11 Analysis – Sensor 5

12. May 2008 US Sensor Calibration 12 Analysis – Sensor 6

13. Analysis – Three sensors 3211/21/41/8 Mean 47.55336.54340.527 Std 28.4331.6122.0825.8424.3916.6 Var 419.81389.7830.89186.65266.781.31

14. Gaussian distribution in six distances Gaussian distribution

15. May 2008 US Sensor Calibration 15 Plan Ultrasonic sensors Calibration Approaches Analysis Conclusion

16. May 2008 US Sensor Calibration 16 Farther is the object from the scene more inaccurate is the measurement of the US sensors. By the contrary, as the object is near the sensors, the measurement is more accurate. There is a sort of linear relationship between the input and the output until the measurement of 1 field. Beyond the 1 field this relationship is lost. Conclusions