The project THRIVE has been funded by the Air Force Office of Scientific Research (AFOSR)
with the aim of investigating the embodiment and socio-cognitive mechanisms in the development of trust between humans and robots involved in interactions and joint tasks.
The work is based on the strategic coupling of developmental robotics modeling and empirical human-robot interaction experiments to evaluate the robot’s embodiment properties
(e.g. voice, emotional, humanoid appearance) and sociocultural mechanisms (e.g. joint attention, joint action, group assimilation) in establishing trust.
Prof. Angelo Cangelosi
is Professor of Machine Learning and Robotics at the University of Manchester (UK) and fellow at the Alan Turing Institute. Previously he was Professor of Artificial Intelligence and Cognition, and founding director, at the Centre for Robotics and Neural Systems at Plymouth University (UK).
He studied psychology and cognitive science at the Universities of Rome La Sapienza and at the University of Genoa, and was visiting scholar at the University of California San Diego and the University of Southampton. Cangelosi's main research expertise is on language grounding and embodiment in humanoid robots, developmental robotics, human-robot interaction, and on the application of neuromorphic systems for robot learning.
Dr. Massimiliano Patacchiola is a Postdoctoral researcher at the University of Edinburgh. He received his PhD in roboitcs and Machine Learning from the University of Plymouth. He has been an intern at Snapchat and has worked in inudstry for several years.
Dr. Debora Zanatto received her PhD in human-robot interaction from the University of Plymouth. She received both her Master's and Bachelor's degree in Psychology from the University of Padua (Italy).
Vinanzi, S., Patacchiola, M., Chella, A., & Cangelosi, A. (2019). Would a robot trust you? Developmental robotics model of trust and theory of mind. Philosophical Transactions of the Royal Society B, 374(1771), 20180032.
Patacchiola, M., & Cangelosi, A. (2017). Head pose estimation in the wild using convolutional neural networks and adaptive gradient methods. Pattern Recognition, 71, 132-143.
Surace, L., Patacchiola, M., Battini Sönmez, E., Spataro, W., & Cangelosi, A. (2017, November). Emotion recognition in the wild using deep neural networks and Bayesian classifiers. In Proceedings of the 19th ACM International Conference on Multimodal Interaction (pp. 593-597). ACM.
Patacchiola, M., & Cangelosi, A. (2016, September). A developmental Bayesian model of trust in artificial cognitive systems. In 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) (pp. 117-123). IEEE.
Zanatto, D., Patacchiola, M., Goslin, J., & Cangelosi, A. (2016, March). Priming anthropomorphism: Can the credibility of humanlike robots be transferred to non-humanlike robots?. In 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 543-544). IEEE.