Industry 4.0, Intelligent Visual Assisted Picking Approach

被引：0

作者：

Arbulu, Mario ^{[1
]}

Mateus, Paola ^{[1
]}

Wagner, Manuel ^{[1
]}

Beltran, Cristian ^{[2
]}

Harada, Kensuke ^{[2
]}

机构：

[1] Univ Nacl Abierta & Distancia UNAD, Bogota 111511, Colombia

[2] Osaka Univ, Grad Sch Engn Sci, Dept Syst Innovat, 1-3 Machikaneyama, Toyonaka, Osaka 5608531, Japan

来源：

MINING INTELLIGENCE AND KNOWLEDGE EXPLORATION, MIKE 2018 | 2018年 / 11308卷

关键词：

Artificial intelligence; Autonomous picking; Artificial vision; Sobel; RANSAC; Screws modeling; OPTIMIZATION;

D O I：

10.1007/978-3-030-05918-7_18

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work deals with a novel intelligent visual assisted picking task approach, for industrial manipulator robot. Intelligent searching object algorithm, around the working area, by RANSAC approach is proposed. After that, the image analysis uses the Sobel operator, to detect the objects configurations; and finally, the motion planning approach by Screw theory on SO(3), allows to pick up the selected object to move it, to a target place. Results and whole approach validation are discussed.

引用

页码：205 / 214

页数：10

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