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http://dx.doi.org/10.9708/jksci.2014.19.10.035

Obstacle Avoidance of Indoor Mobile Robot using RGB-D Image Intensity  

Kwon, Ki-Hyeon (Dept. of Electronics, Information & Communication Engineering, Kangwon National University)
Lee, Hyung-Bong (Dept. of Computer Science & Engineering, Gangneung-Wonju National University)
Publication Information
Journal of the Korea Society of Computer and Information / v.19, no.10, 2014 , pp. 35-42 More about this Journal
Abstract
It is possible to improve the obstacle avoidance capability by training and recognizing the obstacles which is in certain indoor environment. We propose the technique that use underlying intensity value along with intensity map from RGB-D image which is derived from stereo vision Kinect sensor and recognize an obstacle within constant distance. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it. From the comparison experiment between RGB-D data and intensity data, RGB-D data got 4.2% better accuracy rate than intensity data but intensity data got 29% and 31% faster than RGB-D in terms of training time and intensity data got 70% and 33% faster than RGB-D in terms of testing time for LDA and SVM, respectively. So, LDA, SVM have good accuracy and better training/testing time to use for obstacle avoidance based on intensity dataset of mobile robot.
Keywords
RGB-D; Intensity; Stereo Vision; LDA; SVM; Kinect;
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