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Lug Position and Orientation Detection for Robotics Using Maximum Trace Bee Colony

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Abstract
We propose a framework to detect lug position and orientation in robotics that is insensitive to the lug orientation, incorporating a proposed optimization based on the artificial bee colony genetic algorithm. Experimental results show that the proposed optimization method outperformed traditional artificial bee colony and other meta-heuristics in the considered cases and was up to 3 times faster than the traditional approach. The proposed detection framework provided excellent performance to detect lug objects for all test cases.
Author(s)
Phuc Hong NguyenJeong, Jaehoon (Paul)Ahn, Chang Wook
Issued Date
2018-02
Type
Article
DOI
10.1587/transfun.E101.A.549
URI
https://scholar.gist.ac.kr/handle/local/13388
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Citation
Ieice Transactions on Fundamentals of Electronics Communications and Computer Sciences, v.E101A, no.2, pp.549 - 552
ISSN
1745-1337
Appears in Collections:
Department of AI Convergence > 1. Journal Articles
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