Action Conditioned Tactile Prediction: a case study on slip prediction. (arXiv:2205.09430v1 [cs.RO])

Tactile predictive models can be useful across several robotic manipulation
tasks, e.g. robotic pushing, robotic grasping, slip avoidance, and in-hand
manipulation. However, available tactile prediction models are mostly studied
for image-based tactile sensors and there is no comparison study indicating the
best performing models. In this paper, we presented two novel data-driven
action-conditioned models for predicting tactile signals during real-world
physical robot interaction tasks (1) action condition tactile prediction and
(2) action conditioned tactile-video prediction models. We use a magnetic-based …

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