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Automated Rust Removal: Rust Detection and Visual Servo Control

Yang Tian, Guoteng Zhang, Kenji Morimoto, Shugen Ma

Year
2021
Citations
13

Abstract

Rust removal is one of the most hazardous and difficult tasks in the restoration of steel structures such as bridges and towers. Robotic systems provide an alternative technology for performing the task safely and efficiently. The capability to automatically remove rust considering the condition of the rusted area is a significant function of robotic systems. In this paper, we propose an approach for identifying rust as a key technology in the rust removal process. Rust detection can be performed automatically by processing a sequence of camera images. For the utilization of the approach in practical applications, it is designed to be robust to variations in the conditions of rusted areas caused by the presence of working tools or rust powders in the images. A fuzzy force controller that replicates the human behavior during rust removal is designed to construct a visual servo control framework for the rust removal process. The proposed approach is validated using experiments conducted on a rust-grinding robotic prototype.

Keywords

Rust (programming language)ServoController (irrigation)Fuzzy logicProcess (computing)Artificial intelligenceServo controlComputer scienceServomechanismImage processing

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