论文标题
在机器人工具任务期间，使用局部几何形状近似进行的迭代表面映射，并进行稀疏测量
Iterative Surface Mapping Using Local Geometry Approximation with Sparse Measurements During Robotic Tooling Tasks
论文作者
论文摘要
我们提出了一种具有成本效益且通用的方法，用于仅使用稀疏测量值绘制未知的3D自由式表面，而机器人操纵器的最终效果则沿着表面移动。几何形状由平面局部近似，该平面由表面上的测量点定义。该方法依赖于线性卡尔曼过滤器，估计了2D网格上每个点的高度。因此，使用径向基函数确定每个网格点的近似协方差，以考虑测量点位置。我们为格栅点提出了不同的更新策略，以利用平面近似的位置与投影方法。通过使用机器人操纵器跟踪表面来实验验证该方法。在运动过程中，三个激光距离传感器安装在最终效应器上，在运动过程中连续测量表面上的测量点，以确定近似平面。结果表明，表面几何形状可以合理地映射，而平均绝对误差低于1 mm。映射误差主要取决于近似区域的大小和表面的曲率。
We present a cost-efficient and versatile method to map an unknown 3D freeform surface using only sparse measurements while the end-effector of a robotic manipulator moves along the surface. The geometry is locally approximated by a plane, which is defined by measured points on the surface. The method relies on linear Kalman filters, estimating the height of each point on a 2D grid. Therefore, the approximation covariance for each grid point is determined using a radial basis function to consider the measured point positions. We propose different update strategies for the grid points exploiting the locality of the planar approximation in combination with a projection method. The approach is experimentally validated by tracking the surface with a robotic manipulator. Three laser distance sensors mounted on the end-effector continuously measure points on the surface during the motion to determine the approximation plane. It is shown that the surface geometry can be mapped reasonably accurate with a mean absolute error below 1 mm. The mapping error mainly depends on the size of the approximation area and the curvature of the surface.
