论文标题
通过膜操作：高分辨率和高度可变形的触觉感应和控制
Manipulation via Membranes: High-Resolution and Highly Deformable Tactile Sensing and Control
论文作者
论文摘要
触觉感应是一种基本的促进技术的促进技术。但是，可变形的传感器在机器人，握住的对象和环境之间引入了复杂的动态，必须考虑进行精细操纵。在这里，我们提出了一种学习软触觉传感器膜动力学的方法，该动态解释了由握把对象和环境之间的物理相互作用引起的传感器变形。我们的方法将膜的感知3D几何形状与本体感受反应扳手结合在一起，以预测以机器人作用为条件的未来变形。从膜的几何形状和反应扳手中回收了抓紧的物体姿势，从触觉观察模型中解除了相互作用动力学。我们在两个现实的接触量任务上基准了我们的方法：用握把标记和手中的绘画。我们的结果表明，与基准相比，明确建模膜动力学可以实现更好的任务性能和对看不见的对象的概括。
Collocated tactile sensing is a fundamental enabling technology for dexterous manipulation. However, deformable sensors introduce complex dynamics between the robot, grasped object, and environment that must be considered for fine manipulation. Here, we propose a method to learn soft tactile sensor membrane dynamics that accounts for sensor deformations caused by the physical interaction between the grasped object and environment. Our method combines the perceived 3D geometry of the membrane with proprioceptive reaction wrenches to predict future deformations conditioned on robot action. Grasped object poses are recovered from membrane geometry and reaction wrenches, decoupling interaction dynamics from the tactile observation model. We benchmark our approach on two real-world contact-rich tasks: drawing with a grasped marker and in-hand pivoting. Our results suggest that explicitly modeling membrane dynamics achieves better task performance and generalization to unseen objects than baselines.
