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• W4376255995 abstract "The purpose of this paper is to solve a series of problems, such as the difficulty in accurately controlling the specific surfaces, and the interference between the laser beam and the part, when the laser is used to clean mechanical parts with complex surfaces by using robots. Firstly, a region segmentation algorithm of the stereo lithography (STL) model was designed, and the feature surfaces of the model were obtained by using the dihedral angle as the criterion. Then the path points which could easily cause interference between the laser beam and the part to be cleaned were detected by the method of ray intersection, and the pose of the robot was modified according to the normal vectors of two non-interference points that were adjacent to the continuous interference points respectively. Finally, the proposed method was validated by scanning path visualization and robot laser cleaning process experiments. The generated path in the unit of feature surface according to the variation components of normal vectors proved the effectiveness of the STL model region segmentation algorithm based on dihedral angle division criteria; the change of the normal vectors of the path points on the current feature surface was continuous and smooth, which meant that the path points did not cause sudden change of the robot pose after the pose correction. The robot cleaned the specific surfaces of the test workpiece safely and effectively in the actual laser cleaning experiments, and the effective cleaning area reached 96.87%, 99.56%, 94.53% and 91.62% of the target cleaning area, which further proved the effectiveness of this study. The method is also useful for the path planning of robots in other processing fields." @default.
• W4376255995 created "2023-05-13" @default.
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• W4376255995 date "2023-05-12" @default.
• W4376255995 modified "2023-10-17" @default.
• W4376255995 title "Path planning and pose correction of robot laser cleaning process for specific surfaces of parts" @default.
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• W4376255995 doi "https://doi.org/10.1007/s00170-023-11535-6" @default.
• W4376255995 hasPublicationYear "2023" @default.
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