Search Results for author: Nathan F. Lepora

Found 7 papers, 2 papers with code

Tactile Image-to-Image Disentanglement of Contact Geometry from Motion-Induced Shear

no code implementations8 Sep 2021 Anupam K. Gupta, Laurence Aitchison, Nathan F. Lepora

In addition, the unsheared tactile images give a faithful reconstruction of the contact geometry that is not possible from the sheared data, and robust estimation of the contact pose that can be used for servo control sliding around various 2D shapes.

Disentanglement Object Reconstruction

Tactile Sim-to-Real Policy Transfer via Real-to-Sim Image Translation

1 code implementation16 Jun 2021 Alex Church, John Lloyd, Raia Hadsell, Nathan F. Lepora

Simulation has recently become key for deep reinforcement learning to safely and efficiently acquire general and complex control policies from visual and proprioceptive inputs.

reinforcement-learning Translation

Towards integrated tactile sensorimotor control in anthropomorphic soft robotic hands

no code implementations5 Feb 2021 Nathan F. Lepora, Andrew Stinchcombe, Chris Ford, Alfred Brown, John Lloyd, Manuel G. Catalano, Matteo Bianchi, Benjamin Ward-Cherrier

In this work, we report on the integrated sensorimotor control of the Pisa/IIT SoftHand, an anthropomorphic soft robot hand designed around the principle of adaptive synergies, with the BRL tactile fingertip (TacTip), a soft biomimetic optical tactile sensor based on the human sense of touch.

Robotics

Goal-Driven Robotic Pushing Using Tactile and Proprioceptive Feedback

no code implementations3 Dec 2020 John Lloyd, Nathan F. Lepora

We evaluate our method by pushing objects across planar and curved surfaces.

Robotics

Spatio-temporal encoding improves neuromorphic tactile texture classification

no code implementations27 Oct 2020 Anupam K. Gupta, Andrei Nakagawa, Nathan F. Lepora, Nitish V. Thakor

With the increase in interest in deployment of robots in unstructured environments to work alongside humans, the development of human-like sense of touch for robots becomes important.

Classification General Classification +1

Deep Reinforcement Learning for Tactile Robotics: Learning to Type on a Braille Keyboard

1 code implementation6 Aug 2020 Alex Church, John Lloyd, Raia Hadsell, Nathan F. Lepora

Artificial touch would seem well-suited for Reinforcement Learning (RL), since both paradigms rely on interaction with an environment.

reinforcement-learning

Threshold Learning for Optimal Decision Making

no code implementations NeurIPS 2016 Nathan F. Lepora

Decision making under uncertainty is commonly modelled as a process of competitive stochastic evidence accumulation to threshold (the drift-diffusion model).

Decision Making Decision Making Under Uncertainty

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