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:基于摄像头的触觉传感器已经展示了在提高机器人执行各种灵巧操作任务的能力上的巨大潜力。它们的使用优点可以归因于其高分辨率触觉数据和3D深度地图重建能力。不幸的是,许多这些触觉传感器使用平坦的触觉表面,仅感应传感器的一个侧面,或者具有臃肿的形态,这使得将传感器与各种机器人夹具进行集成变得困难。在那些具有全向、曲面触觉传感表面的摄像头传感器中,许多不能提供3D深度地图;而那些能够提供3D深度地图的传感器通常需要特定于特定传感器几何形态的光学设计。在这项工作中,我们介绍了GelSight360,这是一种类似于指尖的全向摄像头触觉传感器,能够产生物体变形传感表面的深度地图。此外,我们还介绍了一种新颖的交叉LED照明方案,可以在不同的全向传感器几何形态和尺寸中实现,使传感器可以轻松地被重新配置并附着到不同的不同自由度的夹爪上。通过这项工作,我们使机器人学家能够快速、轻松地定制高分辨率触觉传感器,以适应他们机器人系统的需求。