Progress in robotics and neuroscience is now sufficiently advanced that their main research problems overlap. Our lab facilitates knowledge transfer between engineering and biology by actively researching both fields.

The Tactile Robotics group has three main themes: (i) development and fabrication of novel 3D-printed tactile sensors and hands; (ii) algorithms for active perception, exploration and manipulation with these tactile robots; (iii) interpretation and inspiration of these algorithms and tactile hardware in terms of the computational neuroscience of perception and action.

Development and fabrication of novel 3D-printed tactile sensors and hands

Advances in multi-material 3D-printing mean it is possible for individuals to design and fabricate state-of-the-art tactile robot hands and sensors, offering significant cost and performance advantages over commercial devices. Our lab's interests include:

1) Design, fabrication and open-sourcing of 3D-printed tactile fingertips and hands.

2) Application of robots with tactile capabilities to examine the mechanisms for perceptual decision making in animals and humans.

Selected publications
B. Ward-Cherrier et al. The TacTip project: biomimetic 3d-printed optical tactile sensors, 2017
B. Ward-Cherrier, N. Rojas, N. Lepora. Model-free precise in-hand manipulation with a 3d-printed tactile gripper. IEEE Robotics & Automation Letters, 2017
L. Cramphorn, B. Ward-Cherrier, N. Lepora. A biomimetic fingerprint improves spatial tactile perception. IEEE Robotics & Automation Letters, 2017.
B. Ward-Cherrier et al. Tactile manipulation with a TacThumb integrated on the Open-Hand M2 Gripper. IEEE Robotics & Automation Letters, 2016.
N. Lepora, B. Ward-Cherrier. Tactile quality control with biomimetic active touch. IEEE Robotics & Automation Letters, 2016.
N. Lepora, B. Ward-Cherrier. Superresolution with an optical tactile sensor. IROS, 2015.

Active perception, exploration and manipulation in robot touch

The development of robust and accurate artificial touch is needed for autonomous robotic systems to interact physically with complex environments, underlying the future robotization of broad areas of manufacturing, food production, healthcare and assisted living. My main interests and experience include:

1) Development of a leading framework for biomimetic active touch that combines tactile perception and control based on the neuroscience of active perception.

2) Pioneering the use of superresolution techniques in robot touch to reach unprecedented levels of accuracy with tactile sensors (typically 50x improvement over other methods).

Selected publications
N. Lepora, K. Aquilina, L. Cramphorn. Exploratory tactile servoing with active touch. IEEE Robotics & Automation Letters, 2017.
B. Ward-Cherrier, L. Cramphorn, N. Lepora. Exploiting sensor symmetry for generalized tactile perception in biomimetic touch. IEEE Robotics and Automation Letters, 2017.
C. Yang, N. Lepora. Object exploration using vision and active touch. IROS 2017.
N. Lepora. Biomimetic Active touch with tactile fingertips and whiskers. IEEE Transactions on Haptics, 2016.
U. Martinez-Hernandez et al. Active sensorimotor control for tactile exploration. Robotics and Autonomous Systems, 2016.
N. Lepora et al. Tactile superresolution and biomimetic hyperacuity. IEEE Transactions on Robotics, 2015.
N. Lepora et al. Active Bayesian perception for simultaneous object localization and identification. Robotics: Science and Systems, 2013.
N. Lepora et al. Optimal decision-making in mammals: Insights from a robot study. Royal Society Interface, 2012.
See also letters/conference papers in: IJCNN2010, ICRA2012, IROS2012, ICRA2013, IROS2013, IROS2015, RAL/ICRA 2016, ICRA2016.

Computational neuroscience of perception and action

Our research group is interested in how human and animal perception relates to accounts of decision making from statistics/mathematics, neuroscience, psychology and philosophy. This includes:

1) Understanding perception from the perspective that our brain is embodied in our body, and thus that perceptual choice must encompass also the effect of moving to make a decision.

2) Understanding how sensory and motor systems interrelate in perceptual decision making. This includes functional models of brain areas including the cortico-basal ganglia system and the cerebellum.

3) Advancing statistical and mathematical methods in optimal decision making.

Selected publications
N. Lepora. Threshold Learning for Optimal Decision making. NIPS, 2016.
N. Lepora, G. Pezzulo. Embodied choice: How action influences perceptual decision making. PLoS Computational Biology, 2015.
N. Lepora, K. Gurney. The basal ganglia optimize decision making over general perceptual hypotheses. Neural Computation, 2012.
N. Lepora et al. Optimal decision-making in mammals: Insights from a robot study. Royal Society Interface, 2012.
N. Lepora et al. Sensory prediction or motor control? Application of Marr-Albus type models of cerebellar function to classical conditioning. Frontiers in Computational Neuroscience, 2010.


Biomimetics forms the foundation for my research program on hardware for tactile sensing and algorithms for perception and control. I am also interested in the field and methodology as a whole, and have authored a review and co-edited several proceedings.

Selected publications
N. Lepora et al. The state of the art in biomimetics. Bioinspiration and Biomimetics, 2013
Lead or co-editor for conference proceedings for Biomimetic & Biohybrid Systems (2012-2016)