中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Binocular Stereo Vision Based Obstacle Detection Method for Manipulator

文献类型:会议论文

作者Liu, Qiang; Zhang XX(张晓雪); Liu JG(刘金国); Zhang T(张天); Ni ZY(倪智宇)
出版日期2016
会议名称International Conference on Electrical Engineering and Automation (ICEEA)
会议日期December 18-19, 2016
会议地点Xiamen, China
关键词Binocular stereo vision Obstacle detection Manipulator
页码1-9
通讯作者Liu JG(刘金国)
中文摘要An obstacle detection method is proposed based on binocular stereo vision for manipulator. Firstly, images are preprocessed after camera calibration such as graying and distortion correction. Then, aiming at the defect that feature points are extracted mixed with many edge response points by traditional SIFT (Scale Invariant Feature Transform) algorithm, we propose wavelet transform to extract the edge points, and compare the edge points with feature points to further eliminate unstable feature points. Finally, the effectiveness of the algorithm is verified by obstacle detection and obstacle avoiding experiments. The results demonstrate that the improved SIFT algorithm can remove the edge responses that the DOG operator generates effectively, and improve the stability and anti-noise ability of SIFT algorithm compared with traditional SIFT algorithm.
收录类别CPCI(ISTP)
产权排序1
会议录2016 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND AUTOMATION (ICEEA 2016)
会议录出版者DESTECH PUBLICATIONS, INC
会议录出版地LANCASTER
语种英语
ISSN号2475-885X
ISBN号978-1-60595-407-3
WOS记录号WOS:000406674000073
源URL[http://ir.sia.cn/handle/173321/20866]  
专题沈阳自动化研究所_空间自动化技术研究室
作者单位1.The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.School of Information and Control Engineering, Liaoning Shihua University, Fushun, China
推荐引用方式
GB/T 7714
Liu, Qiang,Zhang XX,Liu JG,et al. Binocular Stereo Vision Based Obstacle Detection Method for Manipulator[C]. 见:International Conference on Electrical Engineering and Automation (ICEEA). Xiamen, China. December 18-19, 2016.

入库方式: OAI收割

来源:沈阳自动化研究所

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