Exploring Visual Control System of Excavator Robot
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摘要: 对Labview建立的挖掘机器人视觉控制系统在目标物发生旋转、比例发生缩放以及光照条件发生改变时无法始终对目标物进行识别与定位的问题,提出了SIFT图像匹配算法。将其特征描述子通过高斯核函数映射到了更高维的特征空间上去,然后在该空间上对其数据进行降维等改进处理。通过Labview中的Matlab script和Read From Spreadsheet File VI节点调用改进后的SIFT M文件,实现了Labview与Matlab的无缝联接。实验表明:Labview 与Matlab混合编程的挖掘机器人视觉控制系统解决了原先系统所存在的问题,其功能更加完善和强大。Abstract: To solve the problem that its visual control system cannot identify and locate the targets all the time when they perform rotation and scaling or when the lighting condition changes, we proposed the SIFT image matching algorithm and mapped its feature descriptors to a high-dimensional feature space through using the Gaussian kernel function, and then enhanced the targets in the feature space, for example, data dimension reduction. The enhanced SIFT image files were invoked into Labview through the Matlab script and read from spreadsheet file VI nodes, thus realizing the seamless connection of Labview with Matlab. The experimental results show that the Labview and Matlab hybrid programming of the excavator robot's visual control system can solve the problems existing in the old system and is more perfect and powerful.
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Key words:
- design of experiments /
- excavator robot /
- image matching /
- Labview /
- MATLAB
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[1] 瞿延华.挖掘机遥控操作系统的研究[D].兰州:兰州理工大学,2008 Qu Y H. The research of excavator robot's remote control system[D]. Lanzhou:Lanzhou University of Technology,2008 (in Chinese) [2] 马颂德,张正友.计算机视觉理论与算法基础[M].北京:科学出版社,2003 Ma S D, Zhang Z Y. Computer vision theory and algorithm[M]. Beijing:Science Press,2003 (in Chinese) [3] 王福斌,刘杰,陈至坤,等.挖掘机器人双目视觉系统标定方法与立体匹配[J].电气技术与自动化,2012,3(1):156-158 Wang F B, Liu J, Chen Z K, et al. Mining robot binocular vision system calibration and stereo matching[J]. Electrical Technology and Automation,2012,3(1):156-158 (in Chinese) [4] 文怀兴,刘晓红.智能挖掘机器人控制系统的研究[J].机械设计与制造,2010,10(1):157-159 Wen H X, Liu X H. The research of intelligent excavator robot's control system[J]. Mechanical Design and Manufacturing,2010,10(1):157-159 (in Chinese) [5] Travis J,Kring J. Labview for everyone[M]. Electronics Industry,2011 [6] Lowe D G. Object recognition from local scale-invari-ant features[C]//Proceedings of the 7th IEEE International Conference on Computer Vision,Kerkyra,Greece,1999 [7] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004,60(2):91-110 [8] 骞森,朱剑英.基于改进的SIFT特征的图像双向匹配算法[J].机械科学与技术,2007,26(9):79-82 Qian S, Zhu J Y. Image bidirectional matching algorithm based on improved SIFT features[J]. Mechanical Science and Technology,2007,26(9):79-82 (in Chinese) [9] Ke Y, Sukthankar R. PCA-SIFT: A more distinctive representation for local image descriptors[C]//Proceedings of the Conference on Computer Cision and Pattern Recognition, Washington,USA,2004:511-517 [10] 柴敬安,廖克俭,李淼,等.Labview和Matlab混合编程方法的研究与实现[J].计算机测量与控制,2008,16(5):737-740 Chai J A, Liao K J, Li M, et al. The research and implementation of Labview and Matlab's hybrid programming[J]. The Computer Measurement and Control,2008,16(5):737-740 (in Chinese)
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