In context
In early 2024, the push toward flexible, in-situ machining of large complex components—such as spacecraft structures and wind turbine blades—was intensifying. Traditional machine tools struggled with the size and variety of these parts, while robotic equipment offered adaptability but lacked robust perception for unstructured environments. This article from the journal Robot captured the state of the art in merging measurement with machining to enable autonomous, accurate processing.
What was reported
The paper reviews four key technologies for measurement-machining integration: measurement data acquisition, machining feature extraction, machining plan generation, and closed-loop control at the end effector. It notes that current practice often relies on external measuring devices like laser trackers or handheld scanners, with manual intervention in data handling—limiting reliability and efficiency.
Examples cited include Tsinghua University's mobile robot for large spacecraft cabin machining and Huazhong University of Science and Technology's robot for in-situ grinding of large wind turbine blades. The authors highlight that weak-rigidity workpieces deform during processing, making online measurement of deformation a persistent challenge.
They also discuss deployment strategies for sensors—mounted externally, on the robot frame or end effector, or on the workpiece—each with trade-offs in accuracy and flexibility. Data processing must handle both known and unknown CAD models, extracting features to align coordinate systems or reconstruct surfaces for CAM path generation.
Why it mattered
This review underscored a critical gap: no mature technical system yet exists for seamlessly integrating measurement and machining on robotic platforms. Closing this gap could enable truly autonomous, in-situ processing of large components, reducing cycle times and improving quality—an important step toward intelligent manufacturing for high-value industries.
“The integration of measurement and machining technology will bring transformation to industrial production.”
Source: 《机器人》期刊 (robot.sia.cn) · Published 2024-02-04 · “机器人化装备测量－加工一体化技术现状及展望”