David Hardman

PhD Student in Robotics

University of Cambridge

Biography

I’m in my final year of a PhD at Cambridge’s Bio-Inspired Robotics Laboratory, building tactile sensors and artificial skins. I was part of the Horizon 2020 SHERO project for self-healing robotics, and the Samsung Global Research Outreach project on tactile perception.

In my spare time I enjoy playing badminton and tennis, and I’m a member of the world-famous Magic Circle.

Download my CV.

Interests

Soft robotics and mechatronics
Optimisation of sensorised skins
Medical automation
Additive manufacturing
ML in large-scale experimentation
Self-healing materials

Education

PhD in Bio-Inspired Robotics, 2020-2024

University of Cambridge
MEng in Mechanics, Materials and Design, 2019-2020

University of Cambridge
BA in Engineering, 2016-2019

University of Cambridge

Experience

PhD Student

Bio-Inspired Robotics Laboratory

Oct 2020 – Present University of Cambridge

Consultant (Health Tech)

The Technology Partnership

Mar 2023 – Jun 2023 Cambridge

Teaching Assistant

Cambridge Centre for International Research

Jun 2021 – Jul 2022 Cambridge

Undergraduate Researcher

Bio-Inspired Robotics Laboratory

Jul 2019 – Sep 2019 University of Cambridge

Engineering Intern

Densitron Technologies Ltd

Jul 2017 – Dec 2017 Sevenoaks

Tutor

Kumon UK

Mar 2013 – Sep 2016 Tonbridge

Featured Publications

Antonia Georgopoulou, David Hardman, Thomas George Thuruthel, Fumiya Iida, Frank Clemens

September, 2023 In Adv. Sci..

Sensorized Skin with Biomimetic Tactility Features based on Artificial Crosstalk of Bimodal Resistive Sensory Inputs

Mimicking the structure of the human skin by combining surface level thermoreceptors with deeper mechanoreceptors. Tactile stimuli are identified using a feedforward neural network.

David Hardman, Thomas George Thuruthel, Fumiya Iida

March, 2023 In Mater. Today Electronics

Tactile Perception in Hydrogel-based Robotic Skins using Data-Driven Electrical Impedance Tomography

A model-free method for the reconstruction of deformations in a hydrogel skin using electrical impedance tomography. The method can be used for damage detection, environmental monitoring, and multi-touch recognition.

Seppe Terryn, David Hardman, Thomas George Thuruthel, Ellen Roels, Fatemeh Sahraeeazartamar, Fumiya Iida

October, 2022 In Adv. Intell. Syst..

Learning-Based Damage Recovery for Healable Soft Electronic Skins

Comparing recalibration methods for a sensorised skin which has damaged and healed in multiple locations, affecting the response of the sensor channels. Transfer learning is used to recover the tactile sensitivity as quickly as possible.

David Hardman, Thomas George Thuruthel, Fumiya Iida

February, 2022 In NPG Asia Mat.

Self-healing ionic gelatin/glycerol hydrogels for strain sensing applications

Development, characterisation, and applications of a healable gelatin-based sensor for soft robotics.

Publications

David Hardman, Fumiya Iida (2024). Controllable Wound Closure in Artificial Skins using Dual-Layer Bioinspired Mechanism. In Robosoft 2024.

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Lorcan Nicholls, David Hardman, Fumiya Iida (2024). Multi-touch Recognition of Hydrogel-based E-skins using Real-world EIT Datasets. In Robosoft 2024.

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Parth Potdar, David Hardman, Elijah Almanzor, Fumiya Iida (2024). High-Speed Tactile Braille Reading via Biomimetic Sliding Interactions. In IEEE RA-L.

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Aleix Costa Cornellà, David Hardman, Leone Costi, Joost Brancart, Guy Van Assche, Fumiya Iida (2023). Variable sensitivity multimaterial robotic e-skin combining electronic and ionic conductivity using electrical impedance tomography. In Sci. Rep..

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David Hardman, Fumiya Iida (2023). How to Fool Your Robot - Designing Exploitable Sensory Systems. In IOP Conf. Ser. Mater. Sci. Eng..

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