Reinforcement Learning Swarm Systems for Autonomous Manufacturing in Unstructured Environments
- Level
- Postgraduate
- Duration
- 3 years full-time
- Mode
- Full-time
- Subject
- Production Engineering
- Location
- United Kingdom
- Next intake
- FEB 2027
Overview
The ‘what’ This PhD will develop reinforcement learning-driven swarm robotic systems that enable multiple robots to collaborate autonomously in unstructured and dynamic manufacturing environments. The ‘why’ Future manufacturing systems must move beyond fixed, highly structured production lines toward flexible, resilient, and reconfigurable environments capable of handling variability in materials, tasks, and layouts. Traditional single-robot automation struggles in such settings due to limited adaptability and scalability. Swarm systems—comprising multiple simple agents coordinating through local interactions— offer a promising solution. However, achieving robust, safe, and efficient coordination in realworld manufacturing remains an open challenge. This project addresses a key question: how can reinforcement learning enable scalable, adaptive swarm intelligence for real-world industrial tasks? Success will support next-generation manufacturing in sectors such as aerospace, construction, and logistics, contributing to productivity, sustainability, and workforce augmentation. The ‘who’ You will be based at Loughborough University, joining a multidisciplinary research team with expertise in robotics, artificial intelligence, and autonomous systems. Supervision will include leading academics in multi-agent systems and intelligent automation, with opportunities to collaborate across UK partner institutions. Industry engagement and sponsorship The project will be developed in collaboration with industrial stakeholders in manufacturing and automation (e.g. system integrators and advanced manufacturing companies). These partners will provide use cases, validation environments, and real-world constraints, with opportunities for industrial placements or secondments. Aims and objectives Methodology (overview) The project will combine simulation, AI, and robotic experimentation: Skills and development You will gain expertise in: You will also develop key transferable skills in teamwork, problem-solving, and working on complex interdisciplinary challenges. Career pathways This PhD will prepare you for careers in: Why Loughborough With links to MIT (Massachusetts Institute of Technology), Loughborough University offers a leading research environment in robotics, intelligent automation, and manufacturing innovation. You will benefit from: 94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021
Entry requirements
| Degree | 2:1 · or above |
|---|
English language requirements
| IELTS | 6.5 overall, no part below 6 |
|---|
The standard University IELTS English language requirement is 6.5 overall with 6.0 in each individual element (reading, writing, listening and speaking).
Fees
International students: £29,500
UK students: £5,238
UK/Home: £5,238
International: £29,500
Start dates
February 2027
Application deadline
31 October 2026
Campus
- Loughborough, United Kingdom
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