Authors:
Kento Sekiya
1
;
Taiki Yano
1
;
Nobutaka Kimura
2
and
Kiyoto Ito
1
Affiliations:
1
Research & Development Group, Hitachi, Ltd., Kokubunji, Tokyo, Japan
;
2
Research & Development Division, Hitachi America, Ltd., Holland, Michigan, U.S.A.
Keyword(s):
Object Recognition, Robot, Depalletizing, Boundary Confidence.
Abstract:
We developed a reliable object recognition method for a rainbow-SKU depalletizing robot. Rainbow SKUs include various types of objects such as boxes, bags, and bottles. The objects’ areas need to be estimated in order to automate a depalletizing robot; however, it is difficult to detect the boundaries between adjacent objects. To solve this problem, we focus on the difference in the shape of the boundaries and propose package-boundary confidence, which assesses whether the recognized boundary correctly corresponds to that of an object unit. This method classifies recognition results into four categories on the basis of the objects’ shape and calculates the package-boundary confidence for each category. The results of our experimental evaluation indicate that the proposed method with slight displacement, which is automatic recovery, can achieve a recognition success rate of 99.0 %. This is higher than that with a conventional object recognition method. Furthermore, we verified that th
e proposed method is applicable to a real-world depalletizing robot by combining package-boundary confidence with automatic recovery.
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