3D视觉引导的机械臂力控曲面打磨方法OA

To address the issues of over-grinding and under-grinding caused by the interaction between geometric inac-curacies and contact forces in complex surface grinding,this study proposes a vision-guided and six-dimensional force-controlled collaborative adaptive grinding method for robotic arms.The system collects real-time point cloud data of the workpiece surface using a 3D structured light camera to generate the initial grinding trajectory,while a six-dimensional force sensor acquires contact force/moment information to dynamically adjust the end-effector pose for compensating surface geometric deviations.A hierarchical control architecture is adopted to achieve collaboration between global vis-ion-based trajectory planning and local force-controlled fine-tuning.Torque feedback is utilized to suppress tool slip-page and improve surface conformity.Additionally,virtual stiffness is adjusted online based on point cloud curvature to avoid overload.In grinding experiments on complex curved workpieces,compared to methods relying solely on visual trajectory tracking or force control,this study significantly reduces Ra to 0.8 μm,decreases force tracking error by 62％,and effectively eliminates contact loss caused by initial pose deviations.