Current PhD Students
Jordan Crawford
“A Systems Engineering Approach for Autonomous Technologies”
Distributed autonomous systems will become more common and pervasive in the future in many areas. The implementation of autonomous systems is complex due to the interactions between human, technical, social and environmental factors. There is a need to investigate these issues using a systems engineering approach and to ensure the design of the technologies are inherently safe, culturally acceptable in the workplace, and beneficial to the society. The thesis will investigate current issues related to autonomous technologies and propose a new framework to design, verify and validate these systems with human-in-the-loop.
Piotr Fratzcak
“Robot Learning with Human Emotions by Means of Immersive Virtual and Augmented Reality”
Ensuring safety and efficiency in human-robot collaboration (HRC) is essential to the future success of Robotic Autonomous Systems (RAS). This thesis exploits novel Immersive Virtual and Augmented Reality (IVAR) environments to assess and improve the suitability HRC in untested and potentially risky manufacturing tasks. The interdisciplinary research will leverage on low-cost IVAR environment and wearable hardware where virtual experiments will be designed to understand human responses in realistic industrial scenarios. This research will develop a functional HRC by enabling the robot to learn and adapt to human responses.
Simon Micheler
“Early-Stage Decision Support for the Implementation of Intelligent Automation”
This research will contribute to the question of how manufacturing companies can identify business cases for intelligent automation. Currently, there is no systematic methodology to assess the critical influencing factors, and their interdependencies, that would need to be considered when implementing intelligent automation in the manufacturing context. A decision support tool for manufacturing businesses, which allows the user to identify business cases for intelligent automation as part of an early stage automation decision will be developed.