JRM Vol.29 No.2 pp. 275-286
doi: 10.20965/jrm.2017.p0275


Current Status and Future Trends on Robot Vision Technology

Manabu Hashimoto*, Yukiyasu Domae**, and Shun’ichi Kaneko***

*Chukyo University
101-2 Yagoto-Honmachi, Showa-ku, Nagoya, Aichi 466-8666, Japan

**Mitsubishi Electric Corporation
8-1-1 Tsukaguchi, Hon-machi, Amagasaki, Hyogo 661-8661, Japan

***Hokkaido University
Kita-14, Nishi-9, Kita-ku, Sapporo 060-0814, Japan

January 31, 2017
February 16, 2017
April 20, 2017
robot vision, object recognition, 3D feature, industrial robot system, future trends
This paper reviews the current status and future trends in robot vision technology. Centering on the core technology of 3-dimensional (3D) object recognition, we describe 3D sensors used to acquire point cloud data and the representative data structures. From the viewpoint of practical robot vision, we review the performance requirements and research trends of important technologies in 3D local features and the reference frames for model-based object recognition developed to address these requirements. Regarding the latest development examples of robot vision technology, we introduce the important technologies according to purpose such as high accuracy or ease-of-use. Then, we describe, as an application example for a new area, a study of general-object recognition based on the concept of affordance. In the area of practical factory applications, we present examples of system development in areas attracting recent attention, including the recognition of parts in cluttered piles and classification of randomly stacked products. Finally, we offer our views on the future prospects of and trends in robot vision.
Intelligent robot classifying randomly stacked items in bin: (a) illustration of robot and setup and (b) actual robot system

Intelligent robot classifying randomly stacked items in bin: (a) illustration of robot and setup and (b) actual robot system

Cite this article as:
M. Hashimoto, Y. Domae, and S. Kaneko, “Current Status and Future Trends on Robot Vision Technology,” J. Robot. Mechatron., Vol.29 No.2, pp. 275-286, 2017.
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Last updated on Apr. 22, 2024