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

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

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May 2008 US Sensor Calibration 1

Ultrasonic Sensors Calibration

Omar A. Daud Truc-Vien T. Nguyen

May 16, 2008

May 2008 US Sensor Calibration 2

Plan

Ultrasonic sensors Calibration Approaches Analysis Conclusion

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

May 2008 US Sensor Calibration 4

Plan

Ultrasonic sensors Calibration Approaches Analysis Conclusion

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

May 2008 US Sensor Calibration 6

Plan

Ultrasonic sensors Calibration Approaches Analysis Conclusion

May 2008 US Sensor Calibration 7

Static Calibration Approach

Object Distance [Cm] Mean Std

field = 60 [Cm] Sensor 4 Sensor 5 Sensor 6 Sensor 4 Sensor 5 Sensor 6

Eighth_field 18,24 12,03 9 14,13 0,12 0

Quarter_field 41,13 19,92 17,85 21,64 0,19 0,33

Half_field 42,22 33,87 31,69 22,32 0,26 0,33

1_field 65,84 56,92 59,68 5,92 3,66 1,61

2_field 59,63 47,31 60,98 18,58 25,58 7,59

3_field 56,67 49,09 55,09 21,56 24,49 12,80

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.

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

May 2008 US Sensor Calibration 9

Plan

Ultrasonic sensors Calibration Approaches Analysis Conclusion

May 2008 US Sensor Calibration 10

Analysis – Sensor 4

May 2008 US Sensor Calibration 11

Analysis – Sensor 5

May 2008 US Sensor Calibration 12

Analysis – Sensor 6

Analysis – Three sensors

3 2 1 1/2 1/4 1/8

Mean 47.5 53 36.5 43 40.5 27

Std 28.43 31.61 22.08 25.84 24.39 16.6

Var 419.81 389.78 30.89 186.65 266.7 81.31

Gaussian distribution in six distances

Gaussian distribution

May 2008 US Sensor Calibration 15

Plan

Ultrasonic sensors Calibration Approaches Analysis Conclusion

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