원문정보
보안공학연구지원센터(IJFGCN)
International Journal of Future Generation Communication and Networking
Vol.9 No.8
2016.08
pp.111-120
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In view of the problem of AS-R autonomous wheeled mobile robot obstacle avoidance, a rapid convergence of sonar and binocular stereovision sensor distance information in order to detect and avoid obstacle algorithm is proposed in this paper. The algorithm first uses binocular camera (CCD) to get three-dimensional image of the real environment, through the stereo matching and V-disparity method which is used to calculate disparity map, then obstacles is extracted by Hough lines detection algorithm, finally we will get information about obstacles and sonar return information with T-S fuzzy neural network fusion, then it will output walking controlled decisions. Experimental results proved that the algorithm is effective and practical.
목차
Abstract
1. Introduction
2. Sonar and Binocular Vision Information Fusion
3. Obstacle Detection Algorithm Based on V-disparity Method
3.1. Polor Correction
3.2. V-disparity Map Construction
3.3. Improved Linear Fitting Based on Hough Detection Method
4. The Experimental Results and Analysis
5. Conclusions
Acknowledgements
References
1. Introduction
2. Sonar and Binocular Vision Information Fusion
3. Obstacle Detection Algorithm Based on V-disparity Method
3.1. Polor Correction
3.2. V-disparity Map Construction
3.3. Improved Linear Fitting Based on Hough Detection Method
4. The Experimental Results and Analysis
5. Conclusions
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보