Autonomous machines, such as autonomous car technologies, are becoming increasingly popular in today’s technological landscape yet are being held to increasingly strict performance and safety standards. “One of the major roadblocks toward implementing UAV’s into full scale-production,” explains Arnett, “is verifying that the machines will consistently perform as expected.”
Arnett’s research will enhance collaborative decision-making control of multiple UAV’s by taking a non-traditional approach to fuzzy logic control systems. His doctoral research efforts will enhance our confidence in UAV’s to perform and operate in a more predictable manner.
Kelly Cohen, PhD, AEEM professor and Arnett’s undergraduate and graduate advisor, inspired Arnett to pursue in-depth research on genetic fuzzy systems. “I recall the specific moment when Professor Cohen introduced me to Nick Ernest’s PhD research on genetic fuzzy systems. Ernest’s research was showing promising results but before the technology could be matured and possibly introduced into real systems, it needed to meet myriad safety and operating standards. My future research will deal with producing and guiding the necessary training of these control systems by identifying key areas where performance specifications are being violated.”