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Camera-based tactile sensing is a low-cost, popular approach to obtain highlydetailed contact geometry information. However, most existing camera-basedtactile sensors are fingertip sensors, and longer fingers often requireextraneous elements to obtain an extended sensing area similar to the fulllength of a human finger. Moreover, existing methods to estimate proprioceptiveinformation such as total forces and torques applied on the finger fromcamera-based tactile sensors are not effective when the contact geometry iscomplex. We introduce GelSight Svelte, a curved, human finger-sized,single-camera tactile sensor that is capable of both tactile and proprioceptivesensing over a large area. GelSight Svelte uses curved mirrors to achieve thedesired shape and sensing coverage. Proprioceptive information, such as thetotal bending and twisting torques applied on the finger, is reflected asdeformations on the flexible backbone of GelSight Svelte, which are alsocaptured by the camera. We train a convolutional neural network to estimate thebending and twisting torques from the captured images. We conduct geldeformation experiments at various locations of the finger to evaluate thetactile sensing capability and proprioceptive sensing accuracy. To demonstratethe capability and potential uses of GelSight Svelte, we conduct an objectholding task with three different grasping modes that utilize different areasof the finger. More information is available on our website:https://gelsight-svelte.alanz.info

GelSight Svelte: A Human Finger-shaped Single-camera Tactile Robot Finger with Large Sensing Coverage and Proprioceptive Sensing