Safe Human-Robot Collaboration Using UWB and AI

The increasing adoption of collaborative robots (cobots) in manufacturing, logistics, healthcare, and industrial environments is transforming the way humans and machines work together. Unlike traditional industrial robots that operate within isolated safety zones, collaborative robots are designed to share workspaces with human operators. Ensuring the safety, reliability, and efficiency of these human-robot interactions remains one of the most significant challenges in modern automation systems.

This PhD project aims to develop intelligent safety and collaboration frameworks using Ultra-Wideband (UWB) technology and Artificial Intelligence (AI) to enable safe and efficient human-robot interaction in dynamic industrial environments. UWB technology offers highly accurate real-time positioning and tracking capabilities, while AI techniques can provide intelligent decision-making, risk assessment, and adaptive robot behaviour.

The research will investigate how UWB-based localization can be integrated with AI algorithms, sensor fusion techniques, and robotic control systems to detect human presence, predict movement patterns, assess potential collision risks, and dynamically adjust robot actions to ensure safe operation. The project may also explore the integration of additional sensing technologies such as computer vision, LiDAR, and Industrial Internet of Things (IIoT) devices to improve situational awareness and system robustness.

The proposed research aligns strongly with Industry 5.0 principles by supporting human-centric, resilient, and sustainable manufacturing systems. Potential application areas include smart factories, warehouse automation, healthcare robotics, logistics, and advanced manufacturing environments.

The successful candidate will gain expertise in robotics, Artificial Intelligence, UWB systems, sensor fusion, Industrial IoT, and autonomous systems. The project is expected to generate multiple high-quality journal and conference publications and provide opportunities for collaboration with industrial partners and international research networks.

Applicants should hold a minimum of a Bachelor's degree or a Master's degree in Robotics, Electronic Engineering, Electrical Engineering, Mechatronics, Automation Engineering, Computer Engineering, Computer Science, Telecommunications Engineering, or a closely related discipline.

The ideal candidate will have an interest in one or more of the following areas:

Robotics and Autonomous Systems
Human-Robot Interaction (HRI)
Artificial Intelligence and Machine Learning
Industrial Automation and Industry 5.0
Ultra-Wideband (UWB) Positioning Systems
Industrial Internet of Things (IIoT)
Sensor Fusion and Intelligent Sensing
Embedded Systems and Edge Computing
Computer Vision and Intelligent Control Systems

Experience in one or more of the following areas would be advantageous but is not essential:

Programming using Python, C/C++, MATLAB, or ROS (Robot Operating System)
Mobile robotics or collaborative robotics (cobots)
Machine learning and data analytics
Wireless communication and localization technologies
Sensor integration and embedded systems development
Computer vision and image processing
FPGA or real-time control systems

The successful candidate should demonstrate:

Strong analytical, mathematical, and problem-solving skills.
An interest in emerging technologies for intelligent automation and smart manufacturing.
The ability to work independently and as part of a multidisciplinary research team.
Good written and verbal communication skills in English.
A strong motivation to conduct innovative research and publish in leading international journals and conferences.

This project is particularly suitable for candidates seeking careers in robotics, intelligent automation, autonomous systems, industrial AI, smart manufacturing, warehouse automation, healthcare robotics, and next-generation human-machine collaboration technologies. The interdisciplinary nature of the project provides an excellent opportunity to develop expertise in Artificial Intelligence, robotics, wireless sensing, Industrial IoT, and Industry 5.0 technologies.

Candidates with backgrounds in Engineering, Computing, Robotics, Automation, Mechatronics, or Applied Mathematics are encouraged to apply.

Self Funded (Scholarship not available. Fees & Materials to be paid by the student.)

If you are interested in submitting an application for this project, please complete an Expression of Interest.

 https://forms.office.com/e/0hCcrv2Gkp