Dr Henrik Hesse
- Assistant Professor (University of Glasgow Singapore)
I am Programme Director & Assistant Professor in Aerospace Engineering with the University of Glasgow in Singapore (UGS). I have a PhD from Imperial College London (2013) where I investigated reduced-order modelling approaches for load control in flexible aircraft and large wind turbines. During my postdoc at ETH Zurich (2014-2016), I developed novel estimation and control methods for the autonomous operation of tethered drones for a wind power prototype system. I have also ventured into robotics focusing on sensor fusion and localisation of unmanned aerial vehicles in GPS-denied environments which led to several titles in robotics competitions. My current research focuses on modelling, design and control of autonomous systems in the context of their practical application.
My research interests focus around the design, development and autonomy of unmanned aerial vehicles covering the following areas.
- Unmanned Aerial Vehicles (Vehicle Design, Industry Applications, Certification)
- Aerial Robotics (SLAM, Sensor Fusion & Control Design)
- Internet of Things (Indoor Localisation, AI & Computer Vision)
- Nonlinear Aeroelasticity (Load Control & Flexible Multibody Dynamics Modelling)
- Flight Mechanics & Control
Please contact me if you would to work or collaborate in the above areas.
We are currently hiring potential PhD students for the industry PhD positions advertised below. Please contact me if you are interested working on these projects, or other projects related to my research interests above.
Industrial PhD Opportunities
Real-Time Prediction of Pedestrian Cluster Movement
Supervisors: Dr Cindy Goh (UGS), Dr Henrik Hesse (UGS)
To ensure the safe operation of Autonomous Vehicles (AV) in urban environments, it is crucial that such vehicles can predict the movement of pedestrians in existing city spaces. Hence, recent literature has seen an increasing effort to predict the action of pedestrians in order to decrease the risk of accidents when in proximity to AVs. However, in cluttered environments, the interaction with a group of pedestrians is also common. The proper handling of occlusions in such a situation is of paramount importance to guarantee the safety of the road actors. In this work, we therefore propose to develop an AI-based framework for the prediction of pedestrian cluster movement in real time. The proposed approach aims to overcome the limitations of existing technologies and enables the safe operation of AVs in urban traffic situations.
Vortex Surfing for Efficient Flight Operations of Aircraft Formations
Supervisors: Dr Henrik Hesse (UGS), Dr Victor Wang (SIT), Dr Kiran Ramesh (UoG)
Formation flight (i.e. flocking) was first observed in birds to improve aerodynamic efficiency and energy conservation through the reduction of induced drag. Emulating these phenomena for aircraft using vortex surfing can result in potential reduction in drag, and hence fuel consumption. This project will develop CFD tools to support the implementation of vortex surfing for practical flight operations, including the proposal of design guidelines for novel aircraft configurations and the improvement of flight operations/planning. This research investigates the wake generation and propagation produced by different aircraft geometries and how these can be effectively modelled using CFD.
Current PhD Students
- Mark Tay - Vision-based navigation, environment mapping and obstacles avoidance using the predefined light source patterns for indoor UAVs