Review on Measurement Schemes for Robotic Machining of Large Components In-situ

doi:10.3901/JME.2022.14.001

Abstract

Abstract: Among the machining schemes for large-scale components, the inclusive mode represented by processing machine tools and the traditional mode of split processing can no longer meet the requirements of high flexibility, high efficiency, and stability and consistency of machining quality. With the advantages of light weight, modularity and flexibility, mobile robots provide an effective solution for efficient and high precision in-situ machining of large and complex components. The in-situ machining process of mobile robots usually consists of three stages:autonomous navigation, precise positioning and in-situ detection of machining quality. The robot is guided to the position to be machined by autonomous navigation system, and the machining is performed after precise positioning, and in-situ detection is performed after the machining is completed to shorten the production cycle time. Around the above process, vision-based and laser-based measurement schemes for in-situ machining of large component robots are reviewed. In the positioning and navigation of mobile robots, vision-based and laser-based measurement systems are widely applied due to their low cost and high data density, respectively. In the precise determination of the relative position of the tool and the workpiece, binocular vision-related theories and applications are well established, and the laser tracker also show its application potential. In the in-situ detection of the surface quality of parts, laser technology-based detection systems are efficient and high accuracy, which makes it the ideal choice for this process. However, there still exists many challenges in the present measurement schemes. And it is difficult for a single measurement method to meet the changing measurement needs, and with the development of artificial intelligence theory, the integration of multiple measurement means is the development trend of measurement methods in the machining of large component robots in-situ.

Key words: mobile robot, in-situ machining, autonomous navigation, precise positioning, surface quality detection

CLC Number:

TG156

HE Yuhao, XIE Fugui, LIU Xinjun, ZHANG Xu. Review on Measurement Schemes for Robotic Machining of Large Components In-situ[J]. Journal of Mechanical Engineering, 2022, 58(14): 1-14.

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