论文标题
FlowControl：基于光流的视觉伺服
FlowControl: Optical Flow Based Visual Servoing
论文作者
论文摘要
单拍的模仿是从单个演示中进行机器人编程的愿景，而不是计算机代码的乏味构造。我们提出了一种实用方法，用于实现操纵任务的单次模仿，利用基于现代学习的光流以执行实时视觉伺服伺服。我们称之为FlowControl的方法不断跟踪演示视频，并使用指定的前景面具来关注感兴趣的对象。使用RGB-D观测值，FlowControl不需要3D对象模型，并且易于设置。 FlowControl从光流中数十年的工作中继承了对视觉外观的强大鲁棒性。我们在一系列问题上展示了流动控制，包括需要非常精确的动作，以及需要概括的能力。
One-shot imitation is the vision of robot programming from a single demonstration, rather than by tedious construction of computer code. We present a practical method for realizing one-shot imitation for manipulation tasks, exploiting modern learning-based optical flow to perform real-time visual servoing. Our approach, which we call FlowControl, continuously tracks a demonstration video, using a specified foreground mask to attend to an object of interest. Using RGB-D observations, FlowControl requires no 3D object models, and is easy to set up. FlowControl inherits great robustness to visual appearance from decades of work in optical flow. We exhibit FlowControl on a range of problems, including ones requiring very precise motions, and ones requiring the ability to generalize.
