论文标题
通过当地控制
Visuotactile Affordances for Cloth Manipulation with Local Control
论文作者
论文摘要
现实世界中的布经常被弄皱，自我封闭或折叠起来，使得诸如角落之类的关键区域不直接抓握，从而使操纵变得困难。我们提出了一个系统，该系统利用视觉和触觉感知来通过抓握和滑动边缘展开布。通过这样做，机器人能够掌握两个相邻的角落，从而实现了随后的操纵任务，例如折叠或悬挂。作为该系统的组成部分，我们开发了触觉感知网络，这些网络分类了边缘是否被掌握并估计边缘的姿势。我们使用边缘分类网络来监督Visuotactile Edge Grasp负担能力网络，该网络可以以90％的成功率掌握边缘。一旦抓住边缘，我们就证明了机器人可以实时使用触觉估计/控制，沿布滑到相邻角。有关视频，请参见http://nehasunil.com/visuotactile/visuotactile.html。
Cloth in the real world is often crumpled, self-occluded, or folded in on itself such that key regions, such as corners, are not directly graspable, making manipulation difficult. We propose a system that leverages visual and tactile perception to unfold the cloth via grasping and sliding on edges. By doing so, the robot is able to grasp two adjacent corners, enabling subsequent manipulation tasks like folding or hanging. As components of this system, we develop tactile perception networks that classify whether an edge is grasped and estimate the pose of the edge. We use the edge classification network to supervise a visuotactile edge grasp affordance network that can grasp edges with a 90% success rate. Once an edge is grasped, we demonstrate that the robot can slide along the cloth to the adjacent corner using tactile pose estimation/control in real time. See http://nehasunil.com/visuotactile/visuotactile.html for videos.
