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Onboard Real-time Object Surface Recognition for a Small Indoor Mobile Platform Based on Surface Component Ratio Histogram

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Abstract

Since a RGB-D sensor provides rich information about the scene, various object recognition schemes and low-level image descriptors can be used to improve the SLAM performance. However, a cleaning robot, which is usually flat and thus the camera is close to the floor, usually only has a partial view of the objects in front of the camera; therefore, conventional object recognition schemes based on the complete view of objects are not suitable. To address this problem, we introduce a novel object surface recognition algorithm based on the proposed surface component ratio histogram (SCRH). SCRH is a surface descriptor which describes the geometrical shape of the partial view of the object. Without any pre-trained model of the objects, SCRH provides a way to deal with the unexpected objects which the robot encounters during the navigation. SCRH was evaluated using several objects lying on the floor of which the identities are not known in advance. The experimental results show that objects are successfully discriminated based on their surfaces and SCRH is robust for object surface recognition.

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Authors and Affiliations

  1. School of Mechanical Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul, 02841, Korea

    Hee-Won Chae & Jae-Bok Song

  2. School of Mechatronics, Korea University, 145 Anam-ro, Seongbuk-ku, Seoul, 02841, Korea

    Hyejun Yu

Authors
  1. Hee-Won Chae
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  2. Hyejun Yu
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  3. Jae-Bok Song
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Corresponding author

Correspondence to Jae-Bok Song.

Additional information

Recommended by Associate Editor Huaping Liu under the direction of Editor Euntai Kim. This research was supported by the (MOTIE) under the Industrial Foundation Technology Development Program, supervised by the (KEIT) (No. 10084589).

Hee-Won Chae received the B.S. degree in Mechanical Engineering from Korea University in 2013. He is now the M.S. and Ph.D. candidate in the School of Mechanical Engineering at Korea University. His research interests include robot navigation, computer vision, and software engineering.

Hyejun Yu received the B.S. degree in School of Robotics from Kwangwoon University in 2015 and the M.S. degree in Mechatronics from Korea University in 2017. His research interests include robot navigation, computer vision, and robot operation system.

Jae-Bok Song received the B.S. and M.S. degrees in Mechanical Engineering from Seoul National Univ., Seoul, Korea, in 1983 and 1985, respectively, and the Ph.D. degree in Mechanical Engineering from MIT, Cambridge, MA, in 1992. He joined the faculty of the Department of Mechanical Engineering, Korea University, Seoul, Korea in 1993. His research interests include robot navigation and the design and control of robotic systems.

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Chae, HW., Yu, H. & Song, JB. Onboard Real-time Object Surface Recognition for a Small Indoor Mobile Platform Based on Surface Component Ratio Histogram. Int. J. Control Autom. Syst. 17, 765–772 (2019). https://doi.org/10.1007/s12555-018-0084-z

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  • DOI: https://doi.org/10.1007/s12555-018-0084-z

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