Adapting Virtual Reality Training Applications by Dynamically Adjusting Visual Aspects
Fabio Genz, MNM-Team, LMU München, Dieter Kranzlmüller, MNM-Team, LMU München · Computer Science Research Notes · 2024
The present work address the question how to design a Virtual Reality (VR) training application for a class of search and navigation tasks that dynamically adapts to users by adjusting visual aspects for visual guidance. We present a theoretical concept that dynamically adjusts visual aspects (lighting, colour) in virtual environments (VE) based on a combination of measuring user behaviour (head position, head orientation) and training performance (training time, error rate). The concept is build on derived requirements for a VR application that trains search and navigation tasks and a combination of previous approaches to meet them. A proof-of-concept (PoC) application was implemented, training order picking of parcels in a warehouse. Though the presented concept is sound as it is based on previous research, future work should conduct user studies to validate the concept with quantitative data.