To address the challenges of low efficiency and inconsistent quality in the finishing of concrete shield segments, this paper proposes an adaptive trajectory planning method for a robotic system utilizing point cloud data. The system integrates an automated guided vehicle (AGV), a six-degree-of-freedom serial manipulator, and a 3D vision system to create an intelligent finishing robot. A "rectangular" offline programming trajectory is employed, coupled with multi-coordinate system transformations for precise path mapping. A 3D camera captures the segment's surface point cloud, which is subsequently registered, fused, and analyzed by a neural network to identify surface irregularities and compute a look-ahead tilt angle for adaptive trajectory compensation. Experimental results demonstrate that our method significantly enhances finishing uniformity and surface quality, offering a viable technical solution for the automated finishing of complex curved components.
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