Enhanced Virtual Reality

Virtual Reality (VR) training is an emerging method, which is widely deployed in more and more applications. Compared with traditional physical training and video games-based training, VR training can not only provide a sense of realism and immersion similar to physical training but can also train at any time and place, saving time and money. However, due to some constraints like lacking reflections of the ambient environment, the realism and immersion of VR training are insufficient. Therefore, in this paper, we propose enhanced VR training which senses the ambient environment and reflects them as dynamic unexpected training tasks to solve the above problems.