Jin-zhou LEI, Ling-bin ZENG, Nan YE. Research on industrial robot alignment technique with monocular vision[J]. Optics and precision engineering, 2018, 26(3): 733-741.
DOI:
Jin-zhou LEI, Ling-bin ZENG, Nan YE. Research on industrial robot alignment technique with monocular vision[J]. Optics and precision engineering, 2018, 26(3): 733-741. DOI: 10.3788/OPE.20182603.0733.
Research on industrial robot alignment technique with monocular vision
Aiming at the problem of precise alignment of industrial arm
an industrial robot alignment method based on monocular vision is proposed. Combining the industrial robot with monocular vision measurement and a specialized hand-eye calibration panel
the method is able to quickly establish the hand-eye relationship between the camera coordinate system and the alignment axis on the robot's end-effector. In the alignment stage
the attitude of the workpiece is obtained by monocular vision system
and then according to the existing hand-eye relationship and datum posture
the position and orientation between the alignment axis and the workpiece of the alignment axis are evaluated. The experimental results show that the average precision of the alignment is better than 0.2° under the measuring distance of 150 mm.
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熊有伦.机器人技术基础[M].武汉:华中科技大学出版社, 1996.
XUN Y L. Fundamentals of Robotics[M]. Wuhan:Huazhong University of Science and Technology Press, 1996. (in Chinese)
徐德, 谭民, 李原.机器人视觉测量与控制[M]. 3版.北京:国防工业出版社, 2016.
XU D, TAN M, LI Y. Visual Measurement and Control for Robots[M]. 3rd ed.. Beijing:National Defense Industry Press, 2016. (in Chinese)
任梦晴. 自动对接检测定位技术研究[D]. 北京: 北京理工大学, 2015.
REN M Q. Detection technology for positioning in automatic joint[D]. Beijing: Beijing Institute of Technology, 2015. (in Chinese)
ZHAN Q, WANG X. Hand-eye calibration and positioning for a robot drilling system[J]. The International Journal of Advanced Manufacturing Technology, 2012, 61(5-8):691-701.
吕游. 视觉引导技术在工业机器人智能抓取中的应用[D]. 合肥: 合肥工业大学, 2009.
LÜ Y. Application of vision guiding technique in intelligent grasp of industrial robot[D]. Hefei: Hefei University of Technology, 2009. (in Chinese)
YANG W H, LIN J R, GAO Y, et al .. Pose measurement system of double shield universal compact TBM[J] . Acta Optica Sinica, 2015, 35(11):1112005. (in Chinese)
孟祥瑞. 新型激光标靶位姿测量系统关键技术研究[D]. 天津: 天津大学, 2014.
MENG X R. Key techniques on new type laser target pose measurement system[D]. Tianjin: Tianjin University, 2014. (in Chinese)
张广军.视觉测量[M].北京:科学出版社, 2008.
ZHANG G J. Visual Measurement[M]. Beijing:Science Press, 2008. (in Chinese)
CHAO ZH CH, FU S H, JIANG G W, et al .. Mono camera and laser rangefinding sensor position-pose measurement system[J]. Acta Optica Sinica, 2011, 31(3):312001. (in Chinese)
马颂德, 张正友.计算机视觉:计算理论与算法基础[M].北京:科学出版社, 1998.
MA S D, ZHANG ZH Y. Computer Vision:Theory and Algorithms[M]. Beijing:Science Press, 1998. (in Chinese)
赵锐. 基于单目视觉的物体位姿测量方法研究[D]. 合肥: 合肥工业大学, 2005.
ZHAO R. Research on measurement method of object's position and orientation based on single hand-eye vision[D]. Hefei: Hefei University of Technology, 2005. (in Chinese)
WEI ZH ZH, GAO M, ZHOU F Q, et al .. Robot extended eye-in-hand calibration method based on an assistant camera[J]. Opto-Electronic Engineering, 2008, 35(9):76-80, 121. (in Chinese)
ZHU W D, MEI B, YAN G R, et al .. Development of a monocular vision system for robotic drilling[J]. Journal of Zhejiang University Science C, 2014, 15(8):593-606.
ZHANG Z. A flexible new technique for camera calibration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11):1330-1334.
ZHAI G, ZHANG J R, ZHANG Y. Linear-monocular vision based on coplanar feature points for space target relative determination[J]. Transactions of Beijing Institute of Technology, 2013, 33(10):1015-1020. (in Chinese)
FISCHLER M A, BOLLES R C. Random sample consensus:a paradigm for model fitting with applications to image analysis and automated cartography[J]. Communications of the ACM, 1981, 24(6):381-395.
LEPETIT V, MORENO-NOGUER F, FUA P. EPnP:An accurate O(n) solution to the PnP problem[J]. International Journal of Computer Vision, 2009, 81(2):155-166.