08/19/2021
By Sokny Long

The Francis College of Engineering, Department of Mechanical Engineering, invites you to attend a proposal defense by Yuan Gao on “Nonlinear Control and Hybrid Filtering of Bipedal Walking."

Ph.D. Student: Yuan Gao
Defense Date: Sept. 1, 2021
Time: 1 - 2:30 p.m. EST
Location: This will be a virtual defense via Zoom. Those interested in attending should contact yuan_gao@student.uml.edu and committee advisor, yan_gu@uml.edu, at least 24 hours prior to the defense to request access to the meeting.

Committee Chair (Advisor): Yan Gu, Assistant Professor, Mechanical Engineering, University of Massachusetts Lowell

Committee Members:

  • Kshitij Jerath, Assistant Professor, Mechanical Engineering, University of Massachusetts Lowell
  • Kelilah Wolkowicz, Assistant Professor, Mechanical Engineering, University of Massachusetts Lowell
  • Zhu Mao, Assistant Professor, Mechanical Engineering, Worcester Polytechnic Institute
  • Xingye Da, General Manager, XPeng Robotics

Brief Abstract:

Control design and state estimation are essential to ensuring the reliability of bipedal robot systems in performing critical real-world tasks such as disaster response and rescue, home assistance, and delivery and courier services. Yet, solving the problems of control and estimation is particularly challenging for bipedal robots mainly due to their complex hybrid nonlinear dynamics. The proposed dissertation research aims to solve these problems for achieving high-performance locomotion by explicitly considering the associated hybrid, nonlinear robot behaviors. The specific goals of the proposed research are: a) deriving a nonlinear control approach that realizes accurate global-position tracking for both single-domain and multi-domain bipedal robot walking; b) creating an invariant filtering method that guarantees rapid error convergence for the hybrid model of bipedal walking over both stationary and dynamic walking surfaces; and c) experimentally validating the proposed controller and estimator designs, as well as their integration, through simulations and experiments on bipedal walking robots.

All interested students and faculty members are invited to attend the online defense via remote access.