Multimodal Tactile Sensing for Intravehicular Robotic Manipulation

Using robotic manipulators instead of astronauts to complete mundane, repetitive tasks aboard a space vehicle carries enormous value for future space missions. However, relevant tasks like accessing densely packed cargo bags or connecting electrical cables require complex dexterous manipulation skills, while being limited to using only on-hand sensors due to the frequency of visual occlusions. Despite extensive research efforts, dexterous manipulation without external cameras has yet to be demonstrated, largely because of a lack of effective tactile fingers. State of the art tactile sensors are limited in their ability to sense over complex finger geometries, sense high resolution force, contact, slip, and micro-slip, and easily integrate into a manipulator. Additionally, given the multimodal nature of human sensing, it is natural to think that multimodal sensing will be valuable to robotics. However, current tactile manipulation is primarily unimodal. In this project, I will develop a multimodal, data-driven tactile finger that is sensorized over the entire finger surface and able to detect force, contact location, vibrations (for slip and texture detection), and temperature change (for material identification). To demonstrate their efficacy for dexterous manipulation, I will integrate the fingers into a hand and demonstrate a cargo bag manipulation task representative of an intravehicular space environment. To my knowledge, this will be the first finger to fuse multiple touch sensing modalities with multimodal learning.

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