Yuan Gao received his B.S. degree in Mechanical Engineering from China Jiliang University in 2014, and M.S. degree in Mechanical Engineering from Arizona State University in 2016. He also worked as a robotic engineer for one and half years at Diverse Automation located in South Carolina. Yuan developed a keen interest in robotics at a very young age. He decided to pursue a Ph.D. degree in robotics at UMASS Lowell after getting exposed to the fascinating research field of robotics during his M.S. study and career. Yuan likes math and programming. He also enjoys skateboarding and playing electric guitar in his free time.
- I'm currently working on nonlinear state estimation for hybrid systems.
- I earned Udacity's Deep Reinforcement Learning NanoDegree certificate! (01/2021)
- I earned Udacity's C++ NanoDegree certificate! (11/2020)
- My paper (second author) Provably Stabilizing Controllers for Quadrupedal Robot Walking on Dynamic Rigid Surfaces is accepted and wins the Best Student Paper Finalist at AIM 2020! (08/2020)
- My paper Impact-Aware Online Motion Planning for Fully-Actuated Bipedal Robotic Walking is accepted! (01/2020)
- My paper Global-Position Tracking Control for Multi-Domain Planar Bipedal Robotic Walking is accepted! (06/2019)
- Our research on using 5G to remotely control legged robots is now reported in Boston Globe, CNET, Robotics Business Review, and NPR's wbur. (05/2019)
- I lead a group to receive an award from Verizon and Ericsson to further our participation in MassTLC 5G Robotic Challenge (02/2019)
- My paper Global-Position Tracking Control of a Fully Actuated NAO Bipedal Walking Robot is accepted! (01/2019)
- I joined the TRACE Lab as a Ph.D. student. (02/2018)
I work at the TRACE Lab. My Ph.D. research focuses on state estimation, online motion planning, and nonlinear control of hybrid systems with application to legged robot locomotion.
My goal is to develop the legged robotic system to freely navigate through the dangerous, complicated environment to help people.
My expertise includes:
Provably Stabilizing Controllers for Quadrupedal Robot Walking on Dynamic Rigid Surfaces
Time-Dependent Global-Position Tracking Control