As an undergraduate researcher at the Virtual Reality Application Center (VRAC) for half of his undergraduate education Brice worked on projects consisting of unmanned aerial vehicle (UAV) control, 3D visualization of medical data and autonomous FEA analysis.
Increased UAV usage by the Department of Defense has resulted in strained personnel resources; with two trained pilots required to operate one military UAV at any one time and UAV tasks often requiring swapping out of these skilled pilots every few hours due to fatigue. To solve this challenge, a Virtual Battlespace interface has been created by the VRAC where one person has the ability to control multiple UAVs. On this project, Brice designed scenarios for user studies to determine what viewing options, 2D/3D variations, would foster the best decision making environment.
Medical Data Visualization
For a graduate level optimization course Brice worked with a team to determine how to reduce the render time for visualizing 3D MRI data and how to apply windowing. Windowing describes the ability to view data of specific density ranges to examine different tissue types. The major obstacle to widespread use of 3D visualization is that data cannot render in real time due to the vast datasets involved, causing continuing reliance on radiologists analyzing 2D images that represent 3D tissue. A literature review on similar problems involving bin-packing revealed two methods to optimize this process: a logic based computer process or a heuristic evolutionary algorithm. After consideration, particle swarm optimization, a heuristic evolutionary algorithm, was applied to a constrained optimization problem by the group.
A project requiring FEA analysis of many models with slight variations to both the simulated forces and geometric properties of those models required an autonomous approach to efficiently generate this diversity. After performing an initial analysis of existing FEA packages and consulting an FEA professional, a package was chosen. After learning to perform FEA analysis of this system through a scripting language a batch file solution was investigated as an autonomous solution.