Project code



School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Uchenna Ogenyi.


The work on this project will:

  • Investigate and analyse the dynamics of logistics and warehouse operations. Understand the roles, responsibilities, and interactions between human workers and robotic systems in these settings.
  • Develop algorithms and systems to optimize collaborative task allocation and execution between human and robot teams. Focus on improving efficiency and responsiveness in warehouse workflows.
  • Implement adaptive learning mechanisms to enable a robot to learn and adapt its behaviour based on human preferences, work patterns, and changing logistics requirements. This involves real-time adjustments to enhance collaboration.
  • Improve communication channels between humans and robots to ensure seamless information exchange. Utilize technologies such as natural language processing, gesture recognition, and other modalities to enhance communication in a warehouse setting.
  • Implement real-time monitoring of warehouse processes and provide timely feedback to both human and robotic team members. This contributes to proactive decision-making and performance optimization in dynamic environments.


The "Human-Robot Collaboration for Agile Logistics and Warehouse Operations" project is a comprehensive initiative designed to elevate the synergy between humans and robots within dynamic warehouse settings. This multifaceted undertaking addresses various crucial tasks to optimise collaborative efforts in the logistics and warehouse domain. A primary focus is placed on understanding and analysing the intricate dynamics inherent in these operational environments. This involves delving into the roles, responsibilities, and interactions between human workers and robotic systems.

To enhance operational efficiency, the project includes the development of advanced algorithms and systems that facilitate collaborative task optimisation. By leveraging adaptive learning mechanisms, robots can dynamically adjust their behaviour based on human preferences, evolving work patterns, and the dynamic requirements of logistics operations. Communication between humans and robots is a pivotal aspect, prompting the project to improve channels through technologies such as natural language processing and gesture recognition.

User-centric interface design ensures that interfaces align seamlessly with the expectations of warehouse workers and logistics professionals, catering to diverse user groups. The project further aims to identify and automate tasks within logistics and warehouse operations, enhancing overall efficiency and coordination between human and robotic team members. Ethical considerations, regulatory compliance, and validation through simulations and real-world trials round out the project's holistic approach, ultimately contributing to a transformative collaboration between humans and robots in agile logistics and warehouse operations.



Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (conditions apply).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.

Applicants should possess an understanding of the core principles in robotics, computer vision, and machine learning techniques. A good knowledge of Python/C++ programming, strong analytical skills, and a foundation in computer science or related fields are essential requirements. The ideal candidate must demonstrate the ability to think critically and independently, including the formulation of research problems. Additionally, effective oral and written communication skills, along with proficient time management, are highly valued.


How to apply

We’d encourage you to contact Dr Uchenna Ogenyi ( to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code: COMP6271025