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Instance-Agnostic Geometry and Contact Dynamics Learning
This work presents an instance-agnostic learning framework that fuses vision with dynamics to simultaneously learn shape, pose trajectories, and physical properties via the use of geometry as a shared representation.
Towards Human Haptic Gesture Interpretation for Robotic Systems
We demonstrate high classification accuracies among our proposed gesture definitions on a test set, emphasizing that neural net-work classifiers on the raw data outperform other combinations of feature sets and algorithms.
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