叶片机器人砂带磨抛点云匹配算法优化

为解决机器人磨抛路径中工件坐标系难以计算的问题及校正工件装夹误差,将三维点云配准技术应用到叶片机器人砂带磨抛系统中。由三维激光扫描仪扫描工件型面获得工件点云,采用基于主成分分析(PCA)的全局配准算法和改进的迭代最近点(ICP)算法完成了扫描点云和工件模型离散点云间以及不同工件扫描点云间的匹配,以获取工件坐标系和校正工件装夹误差。相关仿真和试验结果表明,优化后的算法在匹配速度与精度上有了长足改进,且加工后产品精度和质量都能满足实际加工要求。

Optimization of point cloud registration algorithm in robotic belt grinding of turbine blade

Aiming at solving the problem of calculating the workpieee coordinate system in the robot grinding paths and calibrate the clamping error, the 3D point cloud registration technology was applied to the robotic belt grinding system for turbine blades. After acquiring the point cloud of workpiece by 3D laser scanner, the combination of principal component analysis （PCA）algorithm and improved iterative closest point（ICP） algorithm were employed to match the scanning points and discrete points of part model, then the workpiece coordinate system was obtained and the clamping error was known. Simulation and experimental results indicate that the registration speed and accuracy of the optimized algorithm are fully improved, and the machining accuracy and surface quality can meet the actual machining requirements.