Video (Video Jittery Due to OBS Capturing from VR )
Details
Programming Language: C++.
Engine: Unreal 4.
Project Type: University.
Platform: PC & HTC Vive.
Technical Features
Simplex Noise
Simplex Noise is an algorithm created by Ken Perlin. Similar to Perlin noise its creates random data that is incredibly useful in procedural generation. Simplex noise has a few advantages over Perlin noise such as being faster for large amounts of data, producing less unwanted artifacts and when used in three dimensions produces better results. In this project it is used to generate the starting data set.
3D Cellular Automata
Cellular Automata (CA) has been used for many different purposes over the years, from reproducing real world patterns such as snowflakes and seashells to full games such as the Conway’s Game of Life. These examples and the majority of uses of Cellular Automata differ from this project in one key aspect: they are usually 2D. While not being used as often for 3D as it is for 2D, CA is very good at creating cave like patterns in 3D. Starting with data generated using simplex noise the algorithm is run multiple times until distinct cave formations are formed. this data can then be passed to the Marching Cubes algorithm to be transformed into a mesh
Marching Cubes
Marching Cubes is an algorithm used to convert simple data in to 3D meshes. Used initially for medical imaging it has now been used to create a plethora of other things, one of the most common being procedural meshes for games. In my honours project it was used to procedurally generate the cave mesh from an isosurface created using Cellular Automata
Chunk System
Since you don’t want to render an infinite cave at all times a chunk system was necessary so as to allow only a set amount of chunks to be created and shown at once. This was done by defining set cube size and generating multiple of these cubes side by side. Due to the seeded nature of Simplex noise persistent caves were able to be achieved despite being generated as separate individual chunks. A big benefit to this approach is also the fact that it works extremely well with multi-threading.
Multi-Threading
Multi-threading is the process of running operations in parallel using different threads. For this project multiple chunks would be generated at the same time on different threads so as to greatly increase the performance of the real time generation of the cave.
Virtual Reality
The cave was designed to be explored in virtual reality, this meant considering its generation to be well suited to teleportation as well as giving a good sense of presence. Another big consideration was to make sure both the movement around the cave as well as the cave itself didn’t produce nausea. These considerations paid of as at the 2018 Abertay Digital Grad Show many people who who played this project commented that usually VR made them fell ill or nauseous but they felt fine exploring this VR cave.
About
A defining problem upon the consumer release of virtual reality hardware was a lack of content in Virtual Reality games. One way that the content within these games could be improved is the use of Procedural Content Generation. The Aim of this honours project was to investigate whether the use of Procedural Content Generation is a viable and effective technique for improving VR games.
In order to look into the applications of procedural generation in terms of VR and test if it is a viable method for the generation of VR content, an application was created in which you can explore a procedural generated environment in VR. This environment was created through a combination of Marching Cubes, Cellular Automata and Simplex Noise to produce an interesting and immersive world. The application was then user tested to assess the effectiveness of the research project. Qualitative and quantitative data was gathered through user testing and performance testing so that the feedback and results from these tests could be used to determine how viable procedural environments are for use in VR games.
The results of this project demonstrated that while not a perfect answer to VR’s content problems procedurally generated environments where indeed very effective at encouraging exploration, discovery and immersion as well as greatly increasing replayability. However, the results also revealed that a lot of thought and work need to be put into VR performance and gameplay in order to achieve good results using procedural environments. It was fond that using the techniques and methods explored in this project Procedural Content Generation can be achieved that works very well in VR as on top of the expected result of being able to create large interesting environments, it also creates environments that encourage natural exploration and invoke a fantastic sense of wonder and discovery.