SAG Grant Final Report for research trip for OSSTP researchers Amanda Chang '26, Angela Huang '25, Lilo Heinrich '24, and alum Celvi Lisy '23 to the 2023 AIAA ASCEND Conference in Las Vegas, NV 10/22/23-10/25/23.
There are long-standing examples of how engineers’ education in probability and statistics has not been sufficient. This work presents a novel theoretical framework to help teach and study statistical variability. Using this framework, we developed an interview guide and deductive coding scheme to use in interviews with engineering students. Early results from these interviews support our initial hypothesis of a slight induced variability bias.
Autonomously gathering aerial data has many potential applications, from co-scouting with ground robots to providing live field information to dismounted units. The ARL team developed a number of autonomous multirotor capabilities, creating an infrastructure for further work at ARL and at Olin.