Beihang University
Ph. D in Control Science and Engineering, advised by Xiang Yu and Kexin Guo.

Beihang University
M.S. in Control Science and Engineering, advised by Lei Guo.

Northwestern Polytechnical University
B.S. in Computer Science, advised by Derek Hoiem.

Capturing Moving object using onboard sensoring This represents the fastest and most accurate vision-based grasping performance reported in the literature.

Feedback favors the generalization of neural ODEs We present feedback neural networks, showing that a feedback loop can flexibly correct the learned latent dynamics of neural ordinary differential equations (neural ODEs), leading to a prominent generalization improvement.

Millimeter-level pick and peg-in-hole task achieved by aerial manipulator Building upon the philosophy of disturbance rejection, we propose a predictive optimization scheme that allows aerial manipulator to successfully execute millimeter-level flying pick and peg-in-hole task.

Precise End-Effector Control for an Aerial Manipulator Under Composite Disturbances: Theory and Experiments In this work, a composite control scheme is constructed, which consists of the manipulator joint velocity planner and the dynamic controller. The idea is intuitive. The joint velocity is generated to counteract the fluctuation of the aerial platform. Furthermore, the dynamic controller is developed to accurately track the planned joint velocity in the presence of strong coupling and model uncertainties. The proposed scheme guarantees the stability of the close loop system, making our approach especially promising solution for aerial manipulation under composite disturbances.