About the Project
Supervisory team: Dr Mohammad Soorati
As robot swarms increasingly operate alongside people, robots must do more than avoid collisions. They must behave in ways that people find safe, predictable and comfortable. This project investigates how multiple robots can coordinate their collective goals while adapting their behaviour to individual humans, preferences and social expectations in shared spaces.
Robot swarms could support people in homes, workplaces, hospitals and public spaces, but operating safely around humans requires more than collision avoidance. Robots must balance their own objectives with the safety, comfort, expectations and trust of the people sharing their environment.
This project investigates human-centred coordination for multiple robots operating in shared spaces. The research explores how multiple robots can pursue collective tasks while adapting their behaviour to the presence of different people. Rather than treating humans simply as obstacles, the project investigates how robots can account for individual preferences, comfort zones, social expectations and changing human behaviour when deciding where and how to move.
Building on existing work using decentralised multi-agent reinforcement learning for navigation around multiple humans, the project explores questions such as:
- how should a swarm trade off task efficiency against human comfort?
- how can robots learn individual differences in acceptable proximity and behaviour?
- how should robots coordinate when accommodating one person's preferences affects the swarm's task?
- how can a swarm communicate its intentions so that people understand and trust its behaviour?
The research may combine multi-agent reinforcement learning, human-robot interaction, robot navigation and experimental studies with humans, using simulation and physical robot platforms. You'll have opportunities to develop and evaluate novel algorithms and interaction strategies for safe, socially acceptable and trustworthy robot swarms operating in real-world environments. You'll have access to the robotic platforms available in SooratiLab including robot dogs, several ground rovers, quadcopters, robotic arms, etc.
The School of Electronics and Computer Science is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees' well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
Entry requirements
You must have a UK 2:1 honours degree, or its international equivalent, in one of the following:
- computer science
- robotics
- artificial intelligence
- engineering
- human-computer interaction
- psychology
- cognitive science
- a closely related discipline
Essential skills:
- good background in machine learning technogolies including reinforcement learning
- strong interest in human-robot interaction, autonomous systems, robotics or artificial intelligence
- ability to undertake independent research and critically evaluate scientific literature
- strong programming skills, preferably in Python or a comparable language
Fees and funding
We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.
Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.
Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
For more information, please visit our postgraduate research funding pages.
How to apply
You need to:
- choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences
- select Full time or Part time
- search for programme PhD Computer Science (7089)
- add name of the supervisor in section 2 of the application
Applications should include:
- research proposal
- your CV (resumé)
- 2 academic references
- degree transcripts and certificates to date
- English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
For questions about applying, doctoralcollege-admissions@soton.ac.uk.
Project leader
For an initial conversation, M.Soorati@soton.ac.uk.