Automating excavation in mining and construction applications is crucial today, as the supply of skilled operators cannot match market demand. To make control decisions for autonomous excavators, gaze-tracking can be employed by solely extracting key information that skilled operators use in the field during a digging task. A subject will wear a camera that looks into both the eye and the surroundings to collect data. After characterizing the human attention points of a digging task, transition points from digging to picking up can be identified using optical flow. This information will serve to identify appropriate inputs in the control decision process.

I am participating in SuperUROP because I would like to gain advanced research skills within robotics to apply to graduate studies. Last year, I was a UROP student in the D’Arbeloff Lab, and I also took 2.671 (Measurement and Instrumentation), a class that has prepared me to present my research results effectively. I’ m excited by the opportunity to learn more about the software aspects of robotics and training neural networks to improve the robot’s intelligence and ability to mimic human behavior.