论文标题
自我监督的深度视觉伺服涂料可用于高精度钉插入
Self-supervised deep visual servoing for high precision peg-in-hole insertion
论文作者
论文摘要
许多工业组装任务都涉及钉孔，例如插入具有次毫计仪公差的插入，即使在高度校准的机器人细胞中也很具有挑战性。可以采用视觉宣传来提高对系统中不确定性的鲁棒性，但是，最先进的方法要么依赖于准确的3D模型来合成渲染，要么手动参与训练数据。我们提出了一种新型的自我监督的视觉宣传方法，用于高精度钉插入，该方法是完全自动化的，不依赖合成数据。我们证明了其适用于将电子组件插入具有紧密公差的印刷电路板中。我们表明，可以通过我们提出的视觉伺服方法在强大但缓慢的基于力的插入策略之前大幅度地加速钉孔插入，该方法的配置是完全自主的。
Many industrial assembly tasks involve peg-in-hole like insertions with sub-millimeter tolerances which are challenging, even in highly calibrated robot cells. Visual servoing can be employed to increase the robustness towards uncertainties in the system, however, state of the art methods either rely on accurate 3D models for synthetic renderings or manual involvement in acquisition of training data. We present a novel self-supervised visual servoing method for high precision peg-in-hole insertion, which is fully automated and does not rely on synthetic data. We demonstrate its applicability for insertion of electronic components into a printed circuit board with tight tolerances. We show that peg-in-hole insertion can be drastically sped up by preceding a robust but slow force-based insertion strategy with our proposed visual servoing method, the configuration of which is fully autonomous.
