Abstract：To solve the positioning problem of the visual robot, based on the two-dimensional code， a method for solving camera pose was proposed to realize the precise positioning of the visual robot. Using the open source computer vision libracy(OpenCV), the standard positions of the two-dimensional code and the camera were calibrated. The image was preprocessed to obtain the accurate edge contour of the two-dimensional code. The loop traversal and the maximum distance algorithm were used to solve the feature points, and the "pixel mutation" algorithm was used to optimize the edge distortion caused by low pixel. The feature points were used to solve the camera position through coordinate transformation, and the method was tested in actual scenes. The experimental results show that the rotation axis error of the algorithm is plus or minus 0.18 meters with the rotation angle error plus or minus 2 degrees and the total translation error plus or minus 0.02 meters, which can realize accurate and effective vision robot positioning.
PAN S S. Research on augmented reality based on two-dimension code content recognition[J]. Microcontrollers & Embedded Systems, 2020, 20(1):24-26，34.（in Chinese）
［2］
ZHANG Y, ZHANG Y, FAN S W, et al. Indoor positioning and navigation based on two-dimensional code and database[J]. The Journal of Engineering, 2019, 2019(23):8820-8823.
LI S D, CHANG Z L, ZHAO L Y. Based on the positioning device and positioning method of crane operating mechanism of two-dimensional code[J]. Hoisting and Conveying Machinery, 2019(21):101-103.（in Chinese）
［5］
LI M X, LU F, ZHANG H C, et al. Predicting future locations of moving objects with deep fuzzy-LSTM networks [J]. Transportmetrica A: Transport Science, 2020,16(1):119-136.
PAN G C, WANG F, WANG H W, et al. Two-dimensional code image extraction and recognition based on OpenCV and Zbar[J]. Computer Knowledge and Technology, 2019,15(16):191-193.（in Chinese）
［7］
JIANG J, ZENG L C,CHEN B, et al. An accurate and flexible technique for camera calibration[J]. Computing, 2019,101(12):1971-1988.
［8］
ZHANG X L, LIU S G. Contrast preserving image decolorization combining global features and local semantic features [J]. The Visual Computer, 2018,34(6/7/8):1099-1108.
SUN J L, PANG J, ZHANG Z L. Recognition of vehicle license plate locating based on color feature and improved Canny operator[J].Journal of Jilin University(Science Edition),2015,53(4):693-697.（in Chinese）
YU H L, LIU H Y, SU H Q, et al. Method of high temperature structure measurement based on Canny edge detection and Hough transformation algorithm[J].Journal of Jilin University(Science Edition),2014,52(3):519-524.（in Chinese）
［11］
WANG N, HE H K. Adaptive homography-based visual servo for micro unmanned surface vehicles[J]. The International Journal of Advanced Manufacturing Technology, 2019,105(6):4875-4882.
［12］
CITRARO L, MRQUEZ-NEILA P, SAVRRE S, et al. Real-time camera pose estimation for sports fields[J]. Machine Vision and Applications,2020,31(2):346-359.
2021, Vol. 42 
