Online positioning of thin-walled blade with small curvature for robotic flexible polishing based on optimal local feature matching

The uncertainty of the blade's position and attitude in robotic flexible polishing leads to poor accuracy and stability of force-position coupling, resulting in potential issues like over-polishing or under-polishing, significantly impacting the consistency of final polishing quality. The study proposes an online positioning method of thin-walled blade with small curvature for robotic flexible polishing. The novelty of proposed method lies in that it is based on optimal local geometric feature matching between the actual workpiece and CAD model to obtain the actual position and attitude of thin-walled blade with small curvature and limited measurement area, with a positioning accuracy of 0.3164 mm, thus achieving the adaptive optimization of robotic movement trajectory. Firstly, a mathematical model for the adaptive optimization of robotic movement trajectory based on the actual posture of workpiece is established. The theoretical principles of spatial point cloud mapping based on the forward kinematics model of serial-robot, spatial point cloud registration based on dense and sparse point clouds, workpiece posture analysis based on reverse derivation of point cloud transformation are secondly studied to achieve an accurate positioning of workpiece in the robotic workspace. The error sources of proposed positioning method are analyzed and a quantitative mathematical model is established to characterize the positioning accuracy of workpiece. The feasibility and reliability of proposed positioning method are finally validated through a typical experiment. The results demonstrate that the proposed method can achieve an accurate positioning of thin-walled blade with small curvature and limited measurement area and thereby ensuring the consistency of final polishing quality.