Wearable technology in the workplace to enable human-robot interaction

Robots are entering more and more in the workplace. What was before confined to highly automated production lines and isolated production cells in large companies, now is moving into SMEs with robots working side by side with humans. One major problem is a reciprocal understanding during work: while humans know and understand other humans, they usually have no clue about the robots; conversely, the robots have difficulty in understanding what their human partners do and feel. Appropriate feedback cues could provide means of understanding each other’s performance and intention during shared tasks, which is critical in human-human collaboration and even more so in human-robot collaboration.

The objective of this project is the development of a wearable technology for human workers to help the robots interpret and therefore interact with them in a personalised way. This wearable technology will also be used to inform the human about the robot intentions and status through appropriate feedback. Moreover, this wearable tech could also have the function of monitoring the occupational health and safety of the workers, allowing potential problems to be identified and dealt with as early as possible.

Based on the identified requirements, the PhD will design, prototype and evaluate the novel wearable tech and develop data analytics/machine learning approaches to enhance the co-working scenario. They will interact with industry partners to understand the workplace constraints and environment including complying with relevant standards.

The PhD will be working in research labs and will be able to access to equipment resources as appropriate.

Entry requirements
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in robotics, mechatronics, biomedical engineering, or a related subject.

A relevant Master’s degree and/or experience in one or more of the following will be an advantage: computer science, human-robot interaction, robotics, AI and machine learning.