Tyler Toner

Bio

Tyler is a PhD candidate in the department of Mechanical Engineering at the University of Michigan, where he is advised by Prof. Kira Barton and Prof. Dawn Tilbury. Before coming to Michigan, he earned a Bachelor of Mechanical Engineering from Auburn University. At Auburn, he developed an interest in control theory and autonomous systems, leading to work on autonomous tractor trailer platooning at the GPS and Vehicle Dynamics Laboratory and later work on autonomous submarines during two Navy research internships.

His current research is in robot learning and control for systems with limited data. He is interested in understanding how robots can learn from past behaviors to complete new tasks with minimal human intervention, as well as how teams of heterogeneous robots can collaborate efficiently in unstructured environments. Meanwhile, he has led the multi-year planning and development of the robotic systems within Michigan's industry-university collaborative SMART Manufacturing Testbed.

As a research intern at General Motors R&D in Manufacturing Automation Research under the supervision of Dr. Miguel Saez and Dr. Vahidreza Molazadeh, Tyler has studied how data-driven methods, such as deep reinforcement learning and adaptive model predictive can be applied to unstructured automotive assembly tasks, such as wire harness installation.

Tyler has a zeal for mentorship and leadership, having guided multidisciplinary teams, totaling more than 20 master’s-level and undergraduate engineering students, resulting in multiple collaborative publications. He is also an active officer of the Mentorship Committee of the Mechanical Engineering Graduate Council, where he organizes sessions for junior PhD students to rehearse their oral qualification exams with senior peers. He is the recipient of the National Science Foundation Graduate Research Fellowship, the Mechanical Engineering Department Fellowship, and four best-student awards from Auburn University.