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Robotized interior finishing operations with visual feedback

Xin Jiang (School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China)
Xiang Li (Harbin Institute of Technology, Shenzhen, China)

Industrial Robot

ISSN: 0143-991x

Article publication date: 13 September 2021

Issue publication date: 3 January 2022

119

Abstract

Purpose

This paper aims to address the problem of integrating sensor feedback in robotized interior finishing operations. Its motivation is to finally realize automatic operations necessitating no human intervention. A vision-based approach is proposed for monitoring the execution status and changing the action accordingly.

Design/methodology/approach

First, a robotic system is proposed which can realize two typical interior finishing operations, namely, putty applying and wall sanding. Second, a new method based on a deep neural network is proposed to process the visual information capturing the execution status of the interior finishing operations. It helps to determine essential parameters on where should be processed and how to execute the corresponding operation. With the proposed method, vision information is embedded into the execution of interior finishing in a closed loop style.

Findings

The experiments demonstrate the feasibility of the proposal and reveal problems for further improvement of the autonomous interior finishing robot.

Originality/value

This provides an original insight into robotized interior finishing by addressing an attempt on integrating visual feedback into the manual process.

Keywords

Acknowledgements

This work was supported by the following projects: National Natural Science Foundation of China (Grant No. U1813202), Shenzhen and Hong Kong Joint Innovation Project (SGLH20161209145252406). The authors would like to thank Grand Land Robot Co., Ltd for their help in this work.

Citation

Jiang, X. and Li, X. (2022), "Robotized interior finishing operations with visual feedback", Industrial Robot, Vol. 49 No. 1, pp. 141-149. https://doi.org/10.1108/IR-02-2021-0034

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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