Both industry and the research community are becoming more interested in utilizing unmanned, autonomous or semi-autonomous vehicles for missions such as surveillance, reconnaissance, and search-and-rescue. One necessary function in each of these missions is collision avoidance or trajectory deconiction. While many approaches have been theorized and simulated, few have been tested in hardware-in-the-loop systems. The objective of this paper is to present test results of various algorithms for deconiction and collision avoidance in a system of multiple aerial unmanned autonomous vehicles (UAVs). A potential function method is demonstrated as well as model predictive control and avoidance control with infinite barrier functions. Theories describe the different approaches and suggest the key features of each. These algorithms are implemented in real time on ying vehicles operating in an indoor test facility. Identical experiments are performed for each algorithm and results are discussed.