Integration of Robotic Vision and Automatic Tool Changer Based on Sequential Motion Primitive for Performing Assembly Tasks

Zong Yue Deng; Li Wei Kang; Hsin Han Chiang; Hsiao Chi Li

doi:10.1016/j.ifacol.2023.10.175

Integration of Robotic Vision and Automatic Tool Changer Based on Sequential Motion Primitive for Performing Assembly Tasks

Zong Yue Deng^*, Li Wei Kang^*, Hsin Han Chiang, Hsiao Chi Li

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Studies on intelligent robotic manipulation systems have typically focused on the programming efficiency, adaptive control of robotic arms, motion planning of robotic arms, and action diversity of grippers. In this study, a decision tree and visual recognition incorporate into a robotic arm to help it learn complex tasks. This study employed a task tree for the automatic planning of complex tasks, in which a decision-making model was used to generate complex task sets from a pre-built motion dataset in real-time performance. Moreover, the model can analyze the rationality of model steps, introduce new tasks, and perform object analysis. This work applies a support vector machine to identify the state of an object. The model selects a suitable gripper with a rapid gripper switch process by considering the characteristics of the targeting object. This study demonstrated the effectiveness of the proposed approach with suitable intelligence through the assembly task.

Original language	English
Title of host publication	IFAC-PapersOnLine
Editors	Hideaki Ishii, Yoshio Ebihara, Jun-ichi Imura, Masaki Yamakita
Publisher	Elsevier B.V.
Pages	5320-5325
Number of pages	6
Edition	2
ISBN (Electronic)	9781713872344
DOIs	https://doi.org/10.1016/j.ifacol.2023.10.175
Publication status	Published - 2023 Jul 1
Event	22nd IFAC World Congress - Yokohama, Japan Duration: 2023 Jul 9 → 2023 Jul 14

Publication series

Name	IFAC-PapersOnLine
Number	2
Volume	56
ISSN (Electronic)	2405-8963

Conference

Conference	22nd IFAC World Congress
Country/Territory	Japan
City	Yokohama
Period	2023/07/09 → 2023/07/14

Keywords

Robotic arm
flexible automation
robotic vision
task tree
tool changer

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.1016/j.ifacol.2023.10.175

Cite this

Deng, Z. Y., Kang, L. W., Chiang, H. H., & Li, H. C. (2023). Integration of Robotic Vision and Automatic Tool Changer Based on Sequential Motion Primitive for Performing Assembly Tasks. In H. Ishii, Y. Ebihara, J. Imura, & M. Yamakita (Eds.), IFAC-PapersOnLine (2 ed., pp. 5320-5325). (IFAC-PapersOnLine; Vol. 56, No. 2). Elsevier B.V.. https://doi.org/10.1016/j.ifacol.2023.10.175

Integration of Robotic Vision and Automatic Tool Changer Based on Sequential Motion Primitive for Performing Assembly Tasks. / Deng, Zong Yue; Kang, Li Wei ; Chiang, Hsin Han et al.
IFAC-PapersOnLine. ed. / Hideaki Ishii; Yoshio Ebihara; Jun-ichi Imura; Masaki Yamakita. 2. ed. Elsevier B.V., 2023. p. 5320-5325 (IFAC-PapersOnLine; Vol. 56, No. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Deng, ZY, Kang, LW , Chiang, HH & Li, HC 2023, Integration of Robotic Vision and Automatic Tool Changer Based on Sequential Motion Primitive for Performing Assembly Tasks. in H Ishii, Y Ebihara, J Imura & M Yamakita (eds), IFAC-PapersOnLine. 2 edn, IFAC-PapersOnLine, no. 2, vol. 56, Elsevier B.V., pp. 5320-5325, 22nd IFAC World Congress, Yokohama, Japan, 2023/07/09. https://doi.org/10.1016/j.ifacol.2023.10.175

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AB - Studies on intelligent robotic manipulation systems have typically focused on the programming efficiency, adaptive control of robotic arms, motion planning of robotic arms, and action diversity of grippers. In this study, a decision tree and visual recognition incorporate into a robotic arm to help it learn complex tasks. This study employed a task tree for the automatic planning of complex tasks, in which a decision-making model was used to generate complex task sets from a pre-built motion dataset in real-time performance. Moreover, the model can analyze the rationality of model steps, introduce new tasks, and perform object analysis. This work applies a support vector machine to identify the state of an object. The model selects a suitable gripper with a rapid gripper switch process by considering the characteristics of the targeting object. This study demonstrated the effectiveness of the proposed approach with suitable intelligence through the assembly task.

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Integration of Robotic Vision and Automatic Tool Changer Based on Sequential Motion Primitive for Performing Assembly Tasks

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