Computer-vision-guided semi-autonomous concrete crack repair for infrastructure maintenance using a robotic arm

Rui Chen, Cheng Zhou, Li-li Cheng

AI in Civil Engineering ›› 2022, Vol. 1 ›› Issue (1) : 9.

AI in Civil Engineering ›› 2022, Vol. 1 ›› Issue (1) : 9. DOI: 10.1007/s43503-022-00007-7
Original Article

Computer-vision-guided semi-autonomous concrete crack repair for infrastructure maintenance using a robotic arm

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Abstract

Engineering inspection and maintenance technologies play an important role in safety, operation, maintenance and management of buildings. In project construction control, supervision of engineering quality is a difficult task. To address such inspection and maintenance issues, this study presents a computer-vision-guided semi-autonomous robotic system for identification and repair of concrete cracks, and humans can make repair plans for this system. Concrete cracks are characterized through computer vision, and a crack feature database is established. Furthermore, a trajectory generation and coordinate transformation method is designed to determine the robotic execution coordinates. In addition, a knowledge base repair method is examined to make appropriate decisions on repair technology for concrete cracks, and a robotic arm is designed for crack repair. Finally, simulations and experiments are conducted, proving the feasibility of the repair method proposed. The result of this study can potentially improve the performance of on-site automatic concrete crack repair, while addressing such issues as high accident rate, low efficiency, and big loss of skilled workers.

Keywords

Computer vision / Concrete crack repair / Robotic construction / Semi-autonomous / Knowledge base system / Human decision making

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Rui Chen, Cheng Zhou, Li-li Cheng. Computer-vision-guided semi-autonomous concrete crack repair for infrastructure maintenance using a robotic arm. AI in Civil Engineering, 2022, 1(1): 9 https://doi.org/10.1007/s43503-022-00007-7

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Funding
National Natural Science Foundation of China(71821001); Hubei Province, China: Key Technologies and Applications of Intelligent Construction(2020ACA006)

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