FU Zhengyu

I'm a master student in Robotics, Systems and Control at ETH Zürich. Before that, I graduated from The Hong Kong University of Science and Technology with dual majors in Integrative System and Design and Computer Engineering.

From 2021 to 2022, I completed my bachelor thesis at the Robotic Systems Lab (RSL) at ETH Zurich on optimal control solvers for robotics, under the supervision of Prof. Marco Hutter and Dr. Farbod Farshidian .

In the summer of 2022, I was a Robotics Institute Summer Scholar (RISS) in the Robotic Exploration Lab at Carnegie Mellon University, supervised by Prof. Zachary Manchester.

I am a robotics enthusiast with broad interests in optimal control, control theory and applied optimization for agile robotics systems such as quadrupeds and quadrotors.

CV  /  Github  /  LinkedIn

profile photo
Publications
Cerberus: Low-Drift Visual-Inertial-Leg Odometry For Agile Locomotion
Shuo Yang, Zixin Zhang, Zhengyu Fu, Zachary Manchester
ICRA 2023 (Accepted)

An open-source Visual-Inertial-Leg Odometry (VILO) state estimation solution, Cerberus, for legged robots that estimates position precisely on various terrains in real time using a set of standard sensors, including stereo cameras, IMU, joint encoders, and contact sensors.

arXiv

Research
(Quadruped)
Bachelor thesis - Multi-threaded nonlinear MPC with PIPG for Legged Robots

A numerical implementation of a parallelizable QP solver named Proportional-Integral Projected Gradient (PIPG) under the nonlinear MPC (NMPC) framework of OCS2 which verified the feasibility of boosting control frequency by parallel computing.

The implementation has been open sourced as the ocs2_slp package under the ocs2 repository. For more information, please see my Bachelor thesis.


Bachelor thesis
(PDAL)
Primal-Dual Augmented Lagrangian (PDAL) Solver for Model Predictive Control

A novel primal-dual formulation of augmented Lagrangian named PDAL that can greatly mitigate the numerical issue associated with the ill-conditioned Hessian and speed up convergence.


Video | Paper | Code
Block-wise LDL routine - A side project of PDAL

A concise LDL factorization routine dedicated for model predictive control. Loop-unrolling and code generation techniques are utilized to speed up factorization of problems with fixed-horizon.


Code
Projects
(manipulator)
Joint Spatial-Temporal Motion Planning for Manipulators

Many motion planning methods ignore temporal dimension of dynamic obstacles, frequently treating them as static at each timestamp. This approach often leads to becoming stuck in local minima or an inability to find solutions. Through the integration of Safe Interval Path Planning (SIPP) with Trajectory Optimization (TO), the planner can incorporate wait actions between active moves, exploring the temporal dimension of the problem and thereby avoiding certain local minima.

Video

(OCS2)
OCS2 Toolbox - Optimal Control for Switched Systems

I revised the parallelization scheme of the backward pass of different dynamical programming (DDP) in OCS2 which improved the performance be 18%. The pull requests (PRs) are merged into the main branch and the toolbox is available at OCS2.

(Optimal Control)
Motion Planning for Mobile Robots with iLQR: A Model Predictive Control Approach

A MPC-iLQR controller for differential wheeled robots that is capable of reasoning about dynamic obstacles and replanning online.

Video

(Linkage)
Quadruped Walking Mechanism

A mechanical system consisting of four identical planar walking mechanisms and being propelled by friction with the ground.

(Multi-agent)

A control algorithm that uses a group of identical robots to manipulate objects collectively.


(IMU)

A motion capture system based solely on two IMUs attached to the forearm and elbow respectively.

Coursework
(Optimal Control)
Optimal Control (Graduate-level Course)

From this course, I learnt
unconstrained optimization,   Constrained Optimization,   Linear Quadratic Regulator(LQR),   Linear Quadratic Gaussian(LQG),   Convex MPC,   Dynamic Programming(DDP),  
Direct Collocation,   Sequential Quadratic Programming(SQP) and Optimization for Hybrid System


A comprehensive introduction to aerial robots. Topics include rigid-body dynamics, system modeling, control, trajectory planning, sensor fusion, and vision-based state estimation.

Robotics Team
(RoboMaster)

Thanks for the website design