About this position
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.
supervisor
https://www.tudublin.ie/explore/faculties-and-schools/engineering-built-environment/electrical-and-electronic-engineering/people/academic-staff/somayeh-mohammady.php
Self Funded (Scholarship not available. Fees & Materials to be paid by the student.)
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