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On-Site Automatic Construction of Partition Walls with Mobile Robot and Computer Vision

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Proceedings of the 2019 DigitalFUTURES (CDRF 2019)

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Abstract

This paper demonstrates the implementation of an on-site mobile robot platform, equipped with computer vision system, which can automate the process of fabricating and construct standard partition wall with minimum human intervention. On the basis of this research, the following aspects are presented: (1) the physical setup and the customized multifunctional end effector that enables the robot to fabricate customized partition wall on site (2) the digital workflow that analyzes the geometrical information of the building components and generates robot operational code, while at the same time sets up communication between tracked mobile platform, robotic arm and end effector. (3) its capability to assemble wall panels in space accurately and align the structures dynamically through real time computer vision technology. The experiment provides an outlook to the possibilities of high accuracy construction of large scale building components with location aware mobile robot.

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Author information

Authors and Affiliations

  1. Tongji University, Shanghai, China

    Hao Meng, Zhihao Liang & Pengcheng Qi

Authors
  1. Hao Meng
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  2. Zhihao Liang
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  3. Pengcheng Qi
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Corresponding author

Correspondence to Hao Meng .

Editor information

Editors and Affiliations

  1. College of Architecture and Urban Planning, Tongji University, Shanghai, China

    Philip F. Yuan

  2. School of Engineering, RMIT University, Melbourne, Australia

    Yi Min (Mike) Xie

  3. College of Architecture and Urban Planning, Tongji University, Shanghai, China

    Jiawei Yao

  4. College of Architecture and Urban Planning, Tongji University, Shanghai, China

    Chao Yan

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Meng, H., Liang, Z., Qi, P. (2020). On-Site Automatic Construction of Partition Walls with Mobile Robot and Computer Vision. In: Yuan, P., Xie, Y., Yao, J., Yan, C. (eds) Proceedings of the 2019 DigitalFUTURES . CDRF 2019. Springer, Singapore. https://doi.org/10.1007/978-981-13-8153-9_33

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