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A new monocular vision measurement method to estimate 3D positions of objects on floor

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Abstract

A new visual measurement method is proposed to estimate three-dimensional (3D) position of the object on the floor based on a single camera. The camera fixed on a robot is in an inclined position with respect to the floor. A measurement model with the camera’s extrinsic parameters such as the height and pitch angle is described. Single image of a chessboard pattern placed on the floor is enough to calibrate the camera’s extrinsic parameters after the camera’s intrinsic parameters are calibrated. Then the position of object on the floor can be computed with the measurement model. Furthermore, the height of object can be calculated with the paired-points in the vertical line sharing the same position on the floor. Compared to the conventional method used to estimate the positions on the plane, this method can obtain the 3D positions. The indoor experiment testifies the accuracy and validity of the proposed method.

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Author information

Authors and Affiliations

  1. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Ling-Yi Xu, Zhi-Qiang Cao, Peng Zhao & Chao Zhou

  2. University of Chinese Academy of Sciences, Beijing, 101408, China

    Ling-Yi Xu, Zhi-Qiang Cao, Peng Zhao & Chao Zhou

Authors
  1. Ling-Yi Xu
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  2. Zhi-Qiang Cao
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  3. Peng Zhao
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  4. Chao Zhou
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Corresponding author

Correspondence to Zhi-Qiang Cao.

Additional information

This work was supported by National Natural Science Foundation of China (Nos. 61273352 and 61473295), National High Technology Research and Development Program of China (863 Program) (No. 2015AA042307), and Beijing Natural Science Foundation (No. 4161002).

Recommended by Associate Editor Xun Chen

Ling-Yi Xu received the B. Sc. degree in control theory and control engineering from the University of Science and Technology Beijing, China in 2010. Currently, she is a master student in control theory and control engineering at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China.

Her research interest is visual measurement for robots.

ORCID iD: 0000-0003-2984-7849

Zhi-Qiang Cao received the B. Sc.M. S. degrees from Shandong University of Technology, China in 1996 and 1999, respectively. In 2002, he received the Ph.D. degree in control theory and control engineering from Institute of Automation, Chinese Academy of Sciences, China. He is currently a professor in the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China.

His research interests include environmental cognition, robot control and multi-robot coordination.

ORCID iD: 0000-0003-1801-3363

Peng Zhao received the B. Sc. degree in mechanical design and automation science from Beijing Information Science and Technology University, China in 2010. He received the Ph.D. degree in control theory and control engineering at the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China in 2015.

His research interests include multi-robot system and visual servoing.

Chao Zhou received the B. Sc. degree (Hons.) in automation from southeast University, China in 2003, and the Ph.D. degree in control theory and control engineering from the Institute of Automation, Chinese Academy of Sciences, China in 2008. He is currently an associate professor in the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, China.

His research interests include motion control of robots and bio-inspired robotic fish.

ORCID iD: 0000-0003-4461-8075

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Xu, LY., Cao, ZQ., Zhao, P. et al. A new monocular vision measurement method to estimate 3D positions of objects on floor. Int. J. Autom. Comput. 14, 159–168 (2017). https://doi.org/10.1007/s11633-016-1047-6

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  • DOI: https://doi.org/10.1007/s11633-016-1047-6

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