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Pose Error Estimation Using a Cylinder in Scanner-Based Robotic Belt Grinding

机译:使用基于扫描仪的机器带磨削滚动的误差估计

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摘要

Scanner-based robotic grinding has shown great potential for replacing the manual method to achieve efficient and automatic manufacturing. However, its application has been limited by the grinding quality, which is affected by the pose errors between the robot and other workcells (a scanner, a workpiece, and a tool). To improve the pose accuracy, this article proposes a novel estimation method for above three pose errors, where a cylinder is used as the calibration object. Using differential kinematics, the relationship between the hand-eye pose error and the reconstructed error is built. The hand-eye pose error is estimated by scanning and reconstructing a cylinder. An iterative method is presented to find the optimized orientation error vector, avoiding the uncertain error of multiple solutions using the Schmidt method. Based on the speed adjoint transformation, a mathematical model between the workpiece/tool pose errors and grinding error is built. Then, an experimental estimation approach for the workpiece/tool pose errors is presented by shape matching the measured points of the grinded cylinder with the design model. Unlike the traditional static construction method, this method uses large-scale measured points with high measurement accuracy to improve the estimation accuracy and stability and can estimate the pose error caused during the dynamic grinding process, such as vibration and force deformation. Finally, pose error estimation and compensation experiments are performed to verify the feasibility of the proposed method.
机译:扫描仪的机器人磨削已经显示出更换手动方法实现高效和自动制造的潜力。然而,其应用受到磨削质量的限制,这些质量受到机器人和其他工作单元(扫描仪,工件和工具)之间的姿势误差的影响。为了提高姿态精度,本文提出了一种用于高于三个姿势误差的新颖估计方法,其中汽缸用作校准物体。使用差分运动学,构建了手眼姿势误差与重建错误之间的关系。通过扫描和重建气缸估计手眼姿势误差。提出了一种迭代方法以找到优化的方向误差向量,避免使用Schmidt方法的多种解决方案的不确定误差。基于速度伴随变换,构建了工件/刀具姿势误差与研磨错误之间的数学模型。然后,通过将研磨圆筒的测量点与设计模型匹配来呈现工件/刀具姿势误差的实验估计方法。与传统的静态施工方法不同,该方法使用具有高测量精度的大规模测量点,以提高估计精度和稳定性,并且可以估计在动态研磨过程中引起的姿势误差,例如振动和力变形。最后,执行姿势误差估计和补偿实验以验证所提出的方法的可行性。

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