论文标题

使用自动接触,平面限制和自我观察的工业双臂机器人对工业双臂机器人的自动校准

Automatic self-contained calibration of an industrial dual-arm robot with cameras using self-contact, planar constraints, and self-observation

论文作者

Stepanova, Karla, Rozlivek, Jakub, Puciow, Frantisek, Krsek, Pavel, Pajdla, Tomas, Hoffmann, Matej

论文摘要

我们提出了一种结合互补校准方法的机器人运动学校准方法:自我接触,平面约束和自我观察。我们分析了终端效应参数,操纵器的关节偏移以及完整运动链(DH参数)的校准的估计。将结果与激光跟踪器提供的地面真实测量值进行了比较。我们的主要发现是:(1)在隔离互补校准方法时,自我接触方法会产生最佳,最稳定的结果。 (2)在校准误差和估计参数的可观察性方面,多种方法的所有组合总是优于使用任何单一方法。结合更多方法可提供机器人参数,以更好地将其推广到未用于校准的工作区零件。 (3)顺序校准,即首先校准相机,然后是机器人运动学,比所有参数的同时校准更有效。在实际的实验中,我们采用了两个安装在公共基础上的工业操纵器。操纵器配备了手腕上的力/扭矩传感器,并在机器人底座上附有两个摄像头,并带有特殊的最终效应器,并带有基准标记。我们收集了一个用于机器人运动学校准的新综合数据集并使其公开可用。数据集及其分析提供了定量和定性的见解,这些见解超出了这项工作中使用的特定操纵器,并适用于一般而言的机器人运动学校准。

We present a robot kinematic calibration method that combines complementary calibration approaches: self-contact, planar constraints, and self-observation. We analyze the estimation of the end effector parameters, joint offsets of the manipulators, and calibration of the complete kinematic chain (DH parameters). The results are compared with ground truth measurements provided by a laser tracker. Our main findings are: (1) When applying the complementary calibration approaches in isolation, the self-contact approach yields the best and most stable results. (2) All combinations of more than one approach were always superior to using any single approach in terms of calibration errors and the observability of the estimated parameters. Combining more approaches delivers robot parameters that better generalize to the workspace parts not used for the calibration. (3) Sequential calibration, i.e. calibrating cameras first and then robot kinematics, is more effective than simultaneous calibration of all parameters. In real experiments, we employ two industrial manipulators mounted on a common base. The manipulators are equipped with force/torque sensors at their wrists, with two cameras attached to the robot base, and with special end effectors with fiducial markers. We collect a new comprehensive dataset for robot kinematic calibration and make it publicly available. The dataset and its analysis provide quantitative and qualitative insights that go beyond the specific manipulators used in this work and apply to self-contained robot kinematic calibration in general.

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