论文标题
神经接触场：跟踪触觉感应的外部接触
Neural Contact Fields: Tracking Extrinsic Contact with Tactile Sensing
论文作者
论文摘要
我们提出了神经接触场，这种方法将神经场和触觉传感汇集在一起，以解决跟踪对象和环境之间外部接触的问题。知道外部接触发生的位置是迈向可以积极控制下游操作任务的方法的第一步。用于本地化环境联系的先前工作通常假设接触类型（例如点或线路），不会捕获触点/无接触过渡，并且仅适用于基本的几何形状对象。神经接触场是第一种可以跟踪任意多模式外部接触的方法，而无需对接触类型做任何假设。我们的关键见解是估计对象形状潜在空间中任何3D点接触的可能性，考虑到基于视觉的触觉输入，这些输入感知了外部接触引起的局部运动。在实验中，我们发现神经接触场能够定位多个接触贴片，而无需对接触的几何形状做出任何假设，并捕获了在看不见的环境配置中具有看不见的对象的已知对象类别的触点/无接触过渡。除了神经接触场外，我们还释放了模拟外部接触相互作用的YCB-超支 - 触发数据集，以实现该领域的进一步研究。项目页面：https：//github.com/carolinahiguera/ncf
We present Neural Contact Fields, a method that brings together neural fields and tactile sensing to address the problem of tracking extrinsic contact between object and environment. Knowing where the external contact occurs is a first step towards methods that can actively control it in facilitating downstream manipulation tasks. Prior work for localizing environmental contacts typically assume a contact type (e.g. point or line), does not capture contact/no-contact transitions, and only works with basic geometric-shaped objects. Neural Contact Fields are the first method that can track arbitrary multi-modal extrinsic contacts without making any assumptions about the contact type. Our key insight is to estimate the probability of contact for any 3D point in the latent space of object shapes, given vision-based tactile inputs that sense the local motion resulting from the external contact. In experiments, we find that Neural Contact Fields are able to localize multiple contact patches without making any assumptions about the geometry of the contact, and capture contact/no-contact transitions for known categories of objects with unseen shapes in unseen environment configurations. In addition to Neural Contact Fields, we also release our YCB-Extrinsic-Contact dataset of simulated extrinsic contact interactions to enable further research in this area. Project page: https://github.com/carolinahiguera/NCF
