3 citations · 4 across the 5 of their papers we have counts for
11 papers · 1 filter
One-Shot Domain-Adaptive Imitation Learning via Progressive Learning
Dandan Zhang, Wen Fan, John Lloyd +2
Traditional deep learning-based visual imitation learning techniques require a large amount of demonstration data for model training, and the pre-trained models are difficult to ad…
A Robust Controller for Stable 3D Pinching using Tactile Sensing
Efi Psomopoulou, Nicholas Pestell, Fotios Papadopoulos +3
This paper proposes a controller for stable grasping of unknown-shaped objects by two robotic fingers with tactile fingertips. The grasp is stabilised by rolling the fingertips on…
Probabilistic Discriminative Models Address the Tactile Perceptual Aliasing Problem
John Lloyd, Yijiong Lin, Nathan F. Lepora
In this paper, our aim is to highlight Tactile Perceptual Aliasing as a problem when using deep neural networks and other discriminative models. Perceptual aliasing will arise wher…
Tactile Sim-to-Real Policy Transfer via Real-to-Sim Image Translation
Alex Church, John Lloyd, Raia Hadsell +1
Simulation has recently become key for deep reinforcement learning to safely and efficiently acquire general and complex control policies from visual and proprioceptive inputs. Tac…
Towards integrated tactile sensorimotor control in anthropomorphic soft robotic hands
Nathan F. Lepora, Andrew Stinchcombe, Chris Ford +5
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, wit…
Pose-Based Tactile Servoing: Controlled Soft Touch using Deep Learning
Nathan F. Lepora, John Lloyd
This article describes a new way of controlling robots using soft tactile sensors: pose-based tactile servo (PBTS) control. The basic idea is to embed a tactile perception model fo…