Research into analysing the feasibility of using VR headsets to train helicopter pilots is in its infancy. While enough is known about what effects VR headsets have on pilots, a research gap exists in the field of explaining what exactly causes these effects to occur. This thesis aims to develop a visual model that can be used to analytically predict how pilot behaviour will be affected by a changing Field-of-View and explain why these changes occur. The scope of this model is analysing where in the pilot’s vision, the point of most feedback lies, and what happens when this point gets clipped out of view while the pilot controls a two degree-of-freedom helicopter model. Subsequently, human-in-the-loop experiments were carried out where the participants had to do velocity disturbance rejection tasks and pitch disturbance rejection tasks for various fields-of-view, to try and validate the model. It was predicted that the performance for the pitch disturbance rejection task would not be affected by the field-of-view but the performance for the velocity disturbance rejection task would degrade as field-of-view was lowered. Overall, there was no significant trend that emerged from the experiments for either task, but significant insights were gained into the scope of the visual model. Based on these, and other findings, the model did a good job in identifying why performance changes and in setting up future researchers for success in this field.

As climate change becomes more and more apparent, it is necessary to find sustainable methods for future aviation. The battery industry is rapidly developing, allowing for batteries with more power density which make more electric aviation possible. As the average aerobatic flight is only 30-40 minutes, it is the perfect category to test these new electric methods. By using this information, the following mission need and project statement can be formulated.