论文标题
Geltip：用于机器人操纵的手指形光学触觉传感器
GelTip: A Finger-shaped Optical Tactile Sensor for Robotic Manipulation
论文作者
论文摘要
在整个手指上传感接触是机器人在混乱环境中执行操纵任务的重要能力。但是，现有的触觉传感器要么只有平坦的传感表面，要么具有有限的感应区域的兼容尖端。在本文中，我们提出了一种新型的光学触觉传感器Geltip，该传感器被形状为手指，并且可以在其表面的任何位置感觉到接触。该传感器捕获了高分辨率和颜色不变的触觉图像，可以利用这些图像，以提取有关对操纵对象的最终效果相互作用的详细信息。我们的广泛实验表明，GELTIP传感器可以有效地将触点定位在其手指形身体的不同位置，而在最佳情况下，平均而言，平均较小的定位误差约为5 mm，低于1 mm。获得的结果表明，GELTIP传感器具有其全能触觉能力促进动态操纵任务的潜力。有关GELTIP传感器的传感器模型和更多信息，请访问http://danfergo.github.io/geltip。
Sensing contacts throughout the fingers is an essential capability for a robot to perform manipulation tasks in cluttered environments. However, existing tactile sensors either only have a flat sensing surface or a compliant tip with a limited sensing area. In this paper, we propose a novel optical tactile sensor, the GelTip, that is shaped as a finger and can sense contacts on any location of its surface. The sensor captures high-resolution and color-invariant tactile images that can be exploited to extract detailed information about the end-effector's interactions against manipulated objects. Our extensive experiments show that the GelTip sensor can effectively localise the contacts on different locations of its finger-shaped body, with a small localisation error of approximately 5 mm, on average, and under 1 mm in the best cases. The obtained results show the potential of the GelTip sensor in facilitating dynamic manipulation tasks with its all-round tactile sensing capability. The sensor models and further information about the GelTip sensor can be found at http://danfergo.github.io/geltip.
