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dc.contributor.authorAlthoefer, K
dc.contributor.authorLing, Y
dc.contributor.authorLi, W
dc.contributor.authorQian, X
dc.contributor.authorLee, WW
dc.contributor.authorQi, P
dc.date.accessioned2024-01-10T11:24:40Z
dc.date.available2024-01-10T11:24:40Z
dc.date.issued2023-01-01
dc.identifier.isbn9798350323658
dc.identifier.issn1050-4729
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/93709
dc.description.abstractIn conjunction with huge recent progress in cam-era and computer vision technology, camera-based sensors have increasingly shown considerable promise in relation to tactile sensing. In comparison to competing technologies (be they resistive, capacitive or magnetic based), they offer super-high-resolution, while suffering from fewer wiring problems. The human tactile system is composed of various types of mechanoreceptors, each able to perceive and process distinct information such as force, pressure, texture, etc. Camera-based tactile sensors such as GelSight mainly focus on high-resolution geometric sensing on a flat surface, and their force measurement capabilities are limited by the hysteresis and non-linearity of the silicone material. In this paper, we present a miniaturised dome-shaped camera-based tactile sensor that allows accurate force and tactile sensing in a single coherent system. The key novelty of the sensor design is as follows. First, we demonstrate how to build a smooth silicone hemispheric sensing medium with uniform markers on its curved surface. Second, we enhance the illumination of the rounded silicone with diffused LEDs. Third, we construct a force-sensitive mechanical structure in a compact form factor with usage of springs to accurately perceive forces. Our multi-modal sensor is able to acquire tactile information from multi-axis forces, local force distribution, and contact geometry, all in real-time. We apply an end-to-end deep learning method to process all the information.en_US
dc.format.extent12570 - 12575
dc.titleA Miniaturised Camera-based Multi-Modal Tactile Sensoren_US
dc.typeConference Proceedingen_US
dc.identifier.doi10.1109/ICRA48891.2023.10160634
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.volume2023-Mayen_US


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