Research on the System Design and Target Recognition Method of the Rebar-Tying Robot

Author:

Feng Ruocheng12,Jia Youquan12,Wang Ting3,Gan Hongxiao3

Affiliation:

1. China Railway NO. 9 Engineering Group Co., Ltd., Shenyang 110005, China

2. Liaoning Provincial Intelligent Construction Technology Innovation Center for Rail Transit Engineering, Shenyang 110100, China

3. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China

Abstract

In the construction industry, the construction process of rebar tying is highly dependent on manual operation, which leads to a wide range of work areas, high labor intensity, and limited efficiency. Therefore, robot technology for automatic rebar tying has become an inevitable trend in on-site construction. This study aims to develop a planar rebar-tying robot that can achieve autonomous navigation, precise positioning, and efficient tying on a plane rebar mesh without boundaries. Our research covers the overall design of the robot control systems, the selection of key hardware, the development of software platforms, and the optimization of core algorithms. Specifically, to address the technical challenges of accurately recognizing the tying position and status, we propose an innovative two-stage identification method that combines a depth camera and an industrial camera to obtain image information about the area to be tied. The effectiveness of the planar rebar-tying robot system, including the recognition method proposed in this study, was verified by experiments on a rebar mesh demonstration platform. The following application of our robot system in the field of the Shenyang Hunnan Science and Technology City Phase IV project achieved satisfactory performance. It is shown that this research has made a unique and significant innovation in the field of automatic rebar tying.

Funder

National Key R&D Program of China

Science and Technology Research and Development Program of China Railway Corporation Limited

Publisher

MDPI AG

Reference28 articles.

1. Machine learning-based identification and classification of physical fatigue levels: A novel method based on a wearable insole device;Anwer;Int. J. Ind. Ergon.,2023

2. A study on the core confinement method of reinforced concrete piers;Lee;J. Korean Soc. Civ. Eng. A,2004

3. Identification of biomechanical risk factors for the development of lower-back disorders during manual rebar tying;Umer;J. Constr. Eng. Manag.,2017

4. Technological advances in rebar tying jobs: A comparative analysis of the associated yields and illnesses;Aires;Int. J. Civ. Eng.,2015

5. Joint performance in concrete beam-column connections reinforced using sma smart material;Oudah;Eng. Struct.,2017

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