Below is a list of all relevant publications authored by Robotics Forum members.


BibTex format

author = {Ding, Z and Lepora, N and Johns, E},
publisher = {IEEE},
title = {Sim-to-real transfer for optical tactile sensing},
url = {},
year = {2020}

RIS format (EndNote, RefMan)

AB - Deep learning and reinforcement learning meth-ods have been shown to enable learning of flexible and complexrobot controllers. However, the reliance on large amounts oftraining data often requires data collection to be carried outin simulation, with a number of sim-to-real transfer methodsbeing developed in recent years. In this paper, we study thesetechniques for tactile sensing using the TacTip optical tactilesensor, which consists of a deformable tip with a cameraobserving the positions of pins inside this tip. We designeda model for soft body simulation which was implemented usingthe Unity physics engine, and trained a neural network topredict the locations and angles of edges when in contact withthe sensor. Using domain randomisation techniques for sim-to-real transfer, we show how this framework can be used toaccurately predict edges with less than 1 mm prediction errorin real-world testing, without any real-world data at all.
AU - Ding,Z
AU - Lepora,N
AU - Johns,E
PY - 2020///
SN - 2152-4092
TI - Sim-to-real transfer for optical tactile sensing
UR -
ER -