Calibration of fixtures in robotic work cells is essential but also time consuming and error-prone, and poor calibration can easily lead to wasted debugging time in downstream tasks. Contact-based calibration methods let the user measure points on the fixture's surface with a tool tip attached to the robot's end effector. Most methods require the user to manually annotate correspondences on the CAD model, however, this is error-prone and a cumbersome user experience. We propose a correspondence-free alternative: The user simply measures a few points from the fixture's surface, and our method provides a tight superset of the poses which could explain the measured points. This naturally detects ambiguities related to symmetry and uninformative points and conveys this uncertainty to the user. Perhaps more importantly, it provides guaranteed bounds on the pose. The computation of such bounds is made tractable by the use of a hierarchical grid on SE(3). Our method is evaluated both in simulation and on a real collaborative robot, showing great potential for easier and less error-prone fixture calibration.

翻译：机器人工作单元中夹具的标定至关重要，但同时也耗时且易出错，较差的标定容易导致下游任务调试时间的浪费。基于接触的标定方法允许用户使用安装在机器人末端执行器上的工具尖端测量夹具表面上的点。然而，大多数方法要求用户在CAD模型上手动标注对应点，这既容易出错又带来繁琐的用户体验。我们提出一种无需对应点的替代方案：用户只需测量夹具表面上的少量点，而我们的方法能够提供一个紧密的超集，包含所有可能解释这些测量点的位姿。该方法自然能检测出与对称性和非信息点相关的歧义，并将这种不确定性传达给用户。或许更重要的是，它提供了位姿的保证边界。通过使用SE(3)上的层次化网格，使此类边界的计算变得可行。我们在仿真环境和真实协作机器人上评估了该方法，显示出实现更简便、更少出错的夹具标定的巨大潜力。