OCTOBER 19-20, 2012 - YMCA University of Science & Technology

Proceedings of the National Conference on
Trends and Advances in Mechanical Engineering,
YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012
(a) (b) (c)
Fig. 8 Image captured at higher light intensity
Using algorithm proposed in this paper, the experimental results in different illumination conditions are shown
in Fig. 7 and Fig.8. The test results are as given below in Table 1.
Sl. No. Colour Minimum light
intensity(Threshold )
Table 1. Test results
Higher light
intensity(Threshold )
Action taken
By robot
1 Red Any Value less than 225 Any Value less than 255 Localization
2 Blue Below 150 Below 175 Turn towards
Right
3 Green Below 100 Below 125 Turn towards light
As per Table 1, the threshold values are more for higher light intensity when compared to that of minimum light
intensity environmental conditions. According to overall results, higher the light intensity higher values of
threshold can be obtained.
6. Conclusion
In connection with the demand of the robot application, this work proposes colour image detection method for
target object recognition. Using colour image segmentation algorithm in MATLAB to find target object is a
slow process. From the tests it’s recognized that estimation accuracy depends on object colour detection. The
effectiveness of this algorithm was verified through real experiments. Autonomous robot localization and
functionality depends on the image processing of data taken by the camera. Data can be greatly affected by light
energy received from the environment. It can be concluded from the test results; light illumination problem can
be overcome by adjusting the threshold value and improve the robustness and adaptability of the system. Realtime
image processing and camera calibration are future research work needed to improve the estimation
accuracy for the mobile robot.
References
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[3] R. A. BROOKS, 1986, A robust layered control system for a mobile robot, IEEE J. Robot. Automat., vol.
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