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  Mr Jared de Bruin  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

For instructions on how to apply, please see: PhD Studentships: UKRI Centre for Doctoral Training in Socially Intelligent Artificial Agents.


  • Emily Cross: School of Psychology
  • Emma Liying Li: School of Computing Science

It is a clear trend that over the coming decade, we can expect to see quadruped robots, which offer great mobility, become widely adopted across different sectors, including industry, logistics, hospitality, and healthcare/social care. People across these sectors will be expected to work closely alongside such quadruped robots. However, it remains unknown (1) how best humans can effectively interact and collaborate with quadruped robots; and (2) for how to establish and maintain social bonds between human and quadruped robots.

In this project, we aim to tackle the above two challenges. We plan to conduct experiments in the advanced motion capture laboratory with the state-of-the-art quadruped and animal-like robots (e.g., spot from Boston Dynamics, Miro and Aibo). We will also bring some pet dogs into the laboratory for experiments. We will aim to understand what physical behaviours people want to see in quadruped robot companions; what physical behaviours will lead to building social relationships between humans and companion robots; the extent to which these physical behaviours can be implemented into quadruped robots (e.g., Spot, Miro, Aibo, etc).

Proposed methods:

From a computing science perspective, the student will engage with system development and integration (developing operational models of animal behaviors and implementing them on quadruped robot platforms). From psychology/social science perspective, the student will measure human and robot interaction via qualitative measures(such as questionnaires and participatory design interview approaches), non-invasive mobile brain imaging (record human brain activity when interact with the quadruped robots), physical response time, and pupillometry (eye tracking when people engage with these robots).

Expected outcomes and impact

The outcome of this project will be new knowledge, strategies and technologies to support harmonious interaction between humans and quadruped robots. The topics spans Psychology, Neuroscience and Computing Science. Empirical research papers and demos will be published in journals and conferences that reach a wide academic audience, e.g., Psychological Science, Cognition (for psychology/neuroscience audience), ACM Transactions, ACM/IEEE HRI and ACM CHI (for computing science audience) and PNAS for multidisciplinary audience.


[Hua 2021] Huang L., Meng Z., Deng Z., Wang C., Li L., Zhao G. (2021, Oct.) Extracting human behavioral biometrics from robot motions, in Proc. 27th Annual International Conference on Mobile Computing and Networking (MobiCom2021), Oct. 2021. DOI: 10.1145/3447993.3482860)
[Hua 2021] Huang L., Meng Z., Deng Z., Wang C., Li L., Zhao G. (2021, Oct.) Towards verifying the user of motion-controlled robotic arm systems via the robot behavior, IEEE IoT Journal Special Issue on Security, Privacy, and Trustworthiness in Intelligent Cyber-Physical Systems and Internet-of-Things, Oct. 2021. (DOI: 10.1109/JIOT.2021.3121623)
[Cro 2021] Cross, E. S. & Ramsey, R. (2021). Mind meets machine: Toward a cognitive science of human-machine interactions. Trends in Cognitive Sciences. 25(3), 200-212.
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