Nathan F. Lepora a Professor of Robotics & AI who leads Dexterous Robotics Group in Bristol Robotics Laboratory, with 5 PIs and over 30 researchers in robot dexterity. His focus is on dexterous robots with a human-like sense of touch that can interact intelligently with their surroundings. Together with his research group, he has pioneered the use of 3D-printing for easy fabrication of tactile sensors, leading to multiple benefits from open-sourcing the technology to the integration into robot hands and grippers. He has also pioneered the use of deep learning and other advanced AI methods both in simulation and reality to control robots using a high-resolution sense of touch.
He holds a Leverhulme Trust Research Leadership Award on: ‘A Biomimetic Forebrain for Robot Touch’, is a Co-Investigator on the ISCF Made Smarter ‘Research Centre for Smart, Collaborative Industrial Robotics’ and is a Fellow of the Alan Turing Institute. He was editor of ‘Living Machines’ that won the British Medical Association Book Awards and has a popular book on ‘Robots (Findout!)’ with over 100 5*-ratings on Amazon.
Former PhD Students & Postdocs
Uriel Martinez-Hernandez – Lecturer in Robotics, University of Bath
Javier Cabellero – Chief Statistician, General Medical Council
Ben Ward-Cherrier – Lecturer in Robotics & RAEng Fellow, University of Bristol
Elena Gianniccini – Lecturer in Robotics, University of Aberdeen
Emma Roscow – Machine Learning Engineer, Scaled Robotics
Luke Cramphorn – Senior Robotics Research Engineer, Dyson
Anupam Gupta – Lead Robotics Research Engineer, Dyson
Nick Pestell – Data Scientist, Bioinformatics
Kirsty Aquilina – Data Scientist, Aptiv
Jasper James – Senior Robotics Research Engineer, Vaarst
Efi Psomopoulou – Lecturer in Data Science, University of Bristol
Tactile Robotics Lab (now part of Dexterous Robotics)
Robot sensors, hands & systems with a sense of touch
The BRL Tactile Robotics group designs and builds novel dexterous tactile robots from 3D-printed fingertips/hands to entire integrated robot systems.
Our technology is based on the TacTip family of tactile fingertips:
Soft – Multi-material 3D-printed
Biomimetic – like the human sense of touch
Optical – based on using an inner tiny camera
Tactile – measures the intricacies of contact
Artificial Intelligence for robot dexterity
My group also develops artificial intelligence that enables our tactile robots to perceive, explore, manipulate and handle complex objects and environments.
We have pioneered the use of deep learning and other advanced AI methods both in simulation and reality to control robots using a high-resolution sense of touch, which has led to a step change in the capability of robots to interact physically with their surroundings.
Neuroscience of human & animal perceptual & action
My group’s work is also inspired by the neuroscience and psychology of perception and action. Human dexterity eclipses that of all other animals and is fundamental to human intelligence.
We research topics in the neuroscience of natural intelligence, including how animals and humans make perceptual decisions and learn from reinforcement. My interests span from sensory processing and decision making to models of perception and action selection.