Amna Mazen had her sights set on a win for more than a year. The assistant professor of applied computing and manufacturing and mechanical engineering technology has been working on her algorithm for mobile robot navigation since her Ph.D. in robotics at the University of Detroit Mercy. Prior to graduating, Mazen traveled to Yokohama, Japan, for the IEEE International Conference on Robotics and Automation (ICRA) to watch and study the third annual Benchmark Autonomous Robot Navigation Challenge. A year later, as a new Michigan Tech faculty member, she and her team won the challenge by a wide margin.
ICRA, founded in 1984, is one of the largest and most prestigious robotics conferences in the world. At ICRA 2022, researchers from George Mason University, in collaboration with Clearpath Robotics, introduced the Benchmark Autonomous Robot Navigation (BARN) Challenge in order to create an annual benchmark for robotic navigation systems and elevate the performance of autonomous robots in challenging environments. This benchmark for success includes a public dataset of over 300 pregenerated simulated environments, which are used by robotics researchers around the world who put their own algorithms to the test against the formidable simulated obstacles.
The BARN dataset became integral to Mazen's work as a graduate student, as she was developing an algorithm for mobile robot navigation in unknown environments for her doctoral research.
"For my dissertation, I was comparing my algorithm with other algorithms, and I heard about BARN," said Mazen. "Before BARN, what any researcher working in robot navigation was doing was comparing their algorithm against one or two available algorithms and measuring their success against just those two."
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