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School of Electronic Engineering and Computer Science
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  4. Human-Robot Teaming with remotely deployed robot fleets

Human-Robot Teaming with remotely deployed robot fleets

Supervisor: Dr Manolis Chiou

Project Description

Fleets of robots are increasingly deployed across a variety of applications, including disaster response, infrastructure inspection, security, logistics, and healthcare. In these settings, humans remain essential, monitoring and supervising, intervening, and collaborating with robots at different levels of abstraction. These Human-Robot Teams have the potential to combine the strengths and complementary competencies of both agents (i.e., human and robot).

However, enabling seamless Human-Robot Teaming (HRT) with multiple robots presents fundamental challenges: humans and robots must maintain shared situational awareness, coordinate their actions under dynamic conditions, adapt to changing circumstances by dynamically allocating attention and control authority, and ultimately communicate and interact seamlessly at various levels of abstraction. Unlike single-robot systems, fleet operations amplify complexity, as operators face increased cognitive demands and the interaction paradigm must scale beyond one-to-one control towards one-to-many collaboration. Current approaches often fail to support the fluid, adaptive teaming that characterizes effective human-human collaboration.​

This PhD project will address critical challenges in enabling seamless and effective HRT with robot fleets. We seek candidates who will propose and pursue novel research in one or more of the following interconnected directions:

Supervisory interfaces and intelligent support: Develop multimodal interfaces (combining visualizations, gestures, natural language, and auditory channels) and intelligent assistant agents that support operators in supervising fleet operations. These systems will proactively filter information, highlight anomalies, diagnose problems, and recommend interventions to reduce cognitive workload and maintain situational awareness across multiple robots.

Variable Autonomy: Develop frameworks for dynamically adjusting robot levels of autonomy based on task demands, environmental conditions, and human/robot capabilities and state.

Shared Understanding between humans and robots: Develop computational shared mental models and shared situational awareness that enable the HRT to maintain common ground.

Your research direction will be shaped by the synergy between your interests and background, which you will refine into a detailed proposal during the first months of the PhD. We welcome candidates with backgrounds in Computer Science, Engineering, Robotics, Artificial Intelligence, Cognitive Science, or Human-Computer Interaction. Strong programming skills and experience with autonomous systems or human factors research are particularly valuable.

The PhD student will receive tuition fees at the home rate and a London stipend at QMUL stipend rates (currently in 2026/27 of £22,618 per year, to be confirmed for subsequent years) annually during the PhD period, which can span for 3 years. Non-home/non-UK students may apply, but if accepted, they will be responsible for the substantial difference in tuition fees, as no additional funding or fee waiver is available to cover this gap.

For more information about the project, please contact Manolis Chiou (m.chiou@qmul.ac.uk).

 

 

Supervisor

Dr Manolis Chiou (he/his) – m.chiou@qmul.ac.uk

Personal Homepage: https://manolischiou.com/

Co-Supervisor Dimitrios Kollias

https://sites.google.com/view/dimitrioskollias/home?authuser=0

Centre for Multimodal AI
https://www.seresearch.qmul.ac.uk/cmai/people/mchiou/

Centre for Human-Centred Computing
https://www.seresearch.qmul.ac.uk/chcc/people/mchiou/

Centre for Advanced Robotics @ Queen Mary
https://www.robotics.qmul.ac.uk/

How to apply 

Queen Mary is interested in developing the next generation of outstanding researchers and decided to invest in specific research areas. Applicants should submit their application following the instructions at: http://eecs.qmul.ac.uk/phd/how-to-apply/   

The application should include the following: 

  • CV (max 2 pages)  
  • Cover letter (max 4,500 characters) stating clearly in the first page whether you are eligible for a scholarship as a UK resident (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)   
  • Research proposal (max 500 words) 
  • 2 References  
  • Certificate of English Language (for students whose first language is not English)  
  • Other Certificates  

Please note that to qualify as a home student for the purpose of the scholarships, a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship.  For more information please see: (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)  

Application Deadline 

Applications should be submitted by 2nd August 2026, which is the final deadline. However, applications will be reviewed on a rolling basis starting from 26th July 2026, and the position may be filled before the deadline if a suitable candidate is found early. Applicants are therefore encouraged to submit as early as possible.

For general enquiries contact Mrs Melissa Yeo at m.yeo@qmul.ac.uk (administrative enquiries) or Dr Arkaitz Zubiaga at a.zubiaga@qmul.ac.uk (academic enquiries) with the subject “EECS 2026 PhD scholarships enquiry”. 

For specific enquiries, contact Dr Manolis Chiou at m.chiou@qmul.ac.uk

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