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Development of the collaborative robot – human-robot collaboration


School of Biological Sciences

Reading United Kingdom Artificial Intelligence Biomedical Engineering Control Systems Cybernetics Machine Learning

About the Project

Robots work effectively in factories. For example, in car factories, huge robotic arms pick up car parts and join them to the skeleton of the car, working at less than millimetre and millisecond precision. However, still, we do not see a robot working for us, or with us in our daily life. This is due to the fact that robots cannot really work with humans in harmony.

To create a true collaborative robot which can physically cooperate in a task, the robot must be able to anticipate its partner’s behaviour. This can be clearly understood from human-to-human interactions such as manipulating a large object together, or even dancing; any delay in reacting to the partner may cause a breakdown in the collaborative movement. The aim of the PhD project is to develop an artificial interactive agent and a robot which can provide a seamless cooperative experience in predicting the motion of the partner.

This project consists of three main aspects:

1. Understanding of human-to-human interactions: the nature of human interactions will be studied while two humans are collaborating to achieve a common task. Two participants, novice and expert, will be asked to perform collaborative work, and their haptic interactions will be analysed.

2. Development of an interactive expert agent: Using machine learning and nonlinear physics of dynamical systems, an interactive expert agent will be developed to interact with novice participants, transferring a skill set to perform a collaborative task.

3. Implementation of the interactive expert agent on a Baxter robot: We will demonstrate how Baxter, the humanoid robot, can dance with a human partner. This mutual interaction needs the prediction of another's motion, and the ability to harmonise motion with others.

This research spans the areas of complex physical systems, behavioural science and neuroscience, with specific expertise in:

1) non-equilibrium dynamics governing adaptive behaviour in physical and living systems;

2) neural/behavioural mechanisms of the closed brain-body loop for Brain Computer Interfaces (BCI); and

3) mathematical models underpinning behaviour and activity of neural networks. A key focus of this work has been revealing how the closed loop of brain-body systems of humans gives rise to behavioural patterns and cognitive behaviour during interactions with other humans. Techniques include physio-chemical experiments, behavioural experiments, electroencephalogram (EEG) measurement, and mathematical modelling. The group’s specialty is using combinations of EEG and haptic devices to develop novel human-machine interfaces that can be used to investigate brain-body mechanisms.

Lab website is; https://www.sites.google.com/site/complexlivingmachineslab/.

Eligibility: Applicants should have a good degree (minimum of a UK Upper Second (2:1) undergraduate degree or equivalent) in Engineering, Control Engineering, and Machine learning, or a strongly-related discipline. Applicants will also need to meet the University’s English Language requirements. We offer pre-sessional courses that can help with meeting these requirements.

How to apply:

Submit an application for a PhD in Biomedical Engineering at http://www.reading.ac.uk/pgapply.

Further information: http://www.reading.ac.uk/biologicalsciences/SchoolofBiologicalSciences/PhD/sbs-phd.aspx

For informal inquiries please contact Dr Yoshikatsu Hayashi, email:.

School of Biological Sciences, University of Reading:

The University of Reading, located west of London, England, provides world-class research education programs. The University’s main Whiteknights Campus is set in 130 hectares of beautiful parkland, a 30-minute train ride to central London and 40 minutes from London Heathrow airport.

Our School of Biological Sciences conducts high-impact research, tackling current global challenges faced by society and the planet. In 2020, we moved into a stunning new ~£60 million Health & Life Sciences building. This state-of-the-art facility is purpose-built for science research and teaching.

In the School of Biological Sciences, you will be joining a vibrant community of ~180 PhD students representing ~40 nationalities. Our students publish in high-impact journals, present at international conferences, and organise a range of exciting outreach and public engagement activities.

During your PhD at the University of Reading, you will expand your research knowledge and skills, receiving supervision in one-to-one and small group sessions. If English is not your first language, the University's excellent International Study and Language Institute will help you develop your academic English skills.

The University of Reading is a welcoming community for people of all faiths and cultures. We are committed to a healthy work-life balance and will work to ensure that you are supported personally and academically.


Funding Notes

We welcome applications from self-funded students worldwide for this project. If you are applying to an international funding scheme, we encourage you to get in contact as we may be able to support you in your application.

References

[1] Thorne, N., Honisch, J. J., Kondo, T., Nasuto, S. and Hayashi, Y. (2019) Temporal structure in haptic signaling under a cooperative task. Frontiers in Human Neuroscience, 13 (372). ISSN 1662-5161 (http://centaur.reading.ac.uk/87397/) [2] Eberle, H., Nasuto, S. and Hayashi, Y. (2018) Anticipation from sensation: using anticipating synchronisation to stabilise a system with inherent sensory delay. Royal Society Open Science, 5 (3). 171314. ISSN 2054-5703 doi: https://doi.org/10.1098/rsos.171314 (http://centaur.reading.ac.uk/75627/) [3] Nishimura, K., Hayashi, Y., Yano, S. and Kondo, T. (2018) Motor learning through cooperative motor experience. In: International Symposium on Micro-NanoMechatronics and Human Science (MHS), 9-12 Dec 2018, Nagoya, Japan, pp. 1-4. doi: https://doi.org/10.1109/MHS.2018.8886965 (http://centaur.reading.ac.uk/90543/)
Please also see Dr Yoshikatsu Hayashi's academic profile:
http://www.reading.ac.uk/biologicalsciences/SchoolofBiologicalSciences/Meetourteam/staff/y-hayashi.aspx

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