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David A. W. Barton

3 accepted papers

2023

Sim-to-Real Model-Based and Model-Free Deep Reinforcement Learning for Tactile Pushing

RA-L 2023

Object pushing presents a key non-prehensile manipulation problem that is illustrative of more complex robotic manipulation tasks. While deep reinforcement learning (RL) methods have demonstrated impressive learning capabilities using visual input, a lack of tactile sensing limits their capability f

Cited by 24SourceScholar
2019

Shear-invariant Sliding Contact Perception with a Soft Tactile Sensor

ICRA 2019poster

Manipulation tasks often require robots to be continuously in contact with an object. Therefore tactile perception systems need to handle continuous contact data. Shear deformation causes the tactile sensor to output path-dependent readings in contrast to discrete contact readings. As such, in some…

Cited by 15SourceScholar