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Deep Learning for Tactile Understanding From Visual and Haptic Data
[article]
2016
arXiv
pre-print
Robots which interact with the physical world will benefit from a fine-grained tactile understanding of objects and surfaces. Additionally, for certain tasks, robots may need to know the haptic properties of an object before touching it. To enable better tactile understanding for robots, we propose a method of classifying surfaces with haptic adjectives (e.g., compressible or smooth) from both visual and physical interaction data. Humans typically combine visual predictions and feedback from
arXiv:1511.06065v2
fatcat:glnc3odxxvbzbnm2n7bbb4qo3i