Camera-based tactile sensors have shown great promise in enhancing a robot's ability to perform a variety of dexterous manipulation tasks. Advantages of their use can be attributed to the high resolution tactile data and 3D depth map reconstructions they can provide. Unfortunately, many of these tactile sensors use either a flat sensing surface, sense on only one side of the sensor's body, or have a bulky form-factor, making it difficult to integrate the sensors with a variety of robotic grippers. Of the camera-based sensors that do have all-around, curved sensing surfaces, many cannot provide 3D depth maps; those that do often require optical designs specified to a particular sensor geometry. In this work, we introduce GelSight360, a fingertip-like, omnidirectional, camera-based tactile sensor capable of producing depth maps of objects deforming the sensor's surface. In addition, we introduce a novel cross-LED lighting scheme that can be implemented in different all-around sensor geometries and sizes, allowing the sensor to easily be reconfigured and attached to different grippers of varying DOFs. With this work, we enable roboticists to quickly and easily customize high resolution tactile sensors to fit their robotic system's needs.

翻译：基于相机的触觉传感器在提升机器人执行多种灵巧操作任务的能力方面展现出巨大潜力。其优势主要源于能够提供高分辨率触觉数据与三维深度图重建。然而，现有许多触觉传感器要么采用平面感应表面，仅在传感器主体单侧感应，要么外形笨重，难以与多种机器人夹爪集成。那些具备全向曲面感应表面的相机式传感器，大多无法提供三维深度图；即便能够实现，也往往需要针对特定传感器几何结构设计光学方案。本研究提出GelSight360——一种指尖状全向相机式触觉传感器，可生成物体变形传感器表面的深度图。此外，我们引入新型跨LED照明方案，该方案可适配不同全向传感器几何结构与尺寸，使传感器能便捷地重构并安装于不同自由度的夹爪上。本工作使机器人研究人员能够快速、轻松地定制高分辨率触觉传感器以适应其机器人系统需求。