Journal of Guangdong University of Technology ›› 2020, Vol. 37 ›› Issue (05): 31-37.doi: 10.12052/gdutxb.190143

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An Indoor Positioning Method of Monocular Vision Robot Based on Floor Features

Jie Yun-fei, Everett Wang, Zhong You-dong, Zhi Kai-xuan, Xiong Chao-wei   

  1. School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2019-11-20 Online:2020-09-17 Published:2020-09-17

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Abstract: In order to solve the problem of high cost in high-precision robot indoor positioning method, an indoor positioning method based on ground features for monocular vision robot is proposed. This method collects the ground image through the monocular fisheye camera installed on the robot chassis, and after a series of image processing, the relationship between the ground grid straight line and the pose of the camera is used as the observational measurements, then the position information of the robot is obtained by deriving the observation equation and the extended Kalman filter algorithm. Based on the current time position data of the robot and the fixed square size of the ground, a line prediction algorithm is proposed to effectively eliminate the influence of the interference line segment. The experimental results show that the positioning accuracy of the robot indoor positioning method can reach 2 cm, which has good robustness and also can provide a good technical reference for low-cost robot indoor positioning.

Key words: robot indoor positioning, square line, Kalman filtering, image processing, line prediction

CLC Number: 

  • TP242
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