Baozhe Zhang 张宝哲

I am an undergraduate student at The Chinese University of Hong Kong, Shenzhen. I am interested in robotics, especially in aerial robots. I am also interested in motion planning, advanced control, and integrating machine learning methods into classical robot working pipelines. I love C++ and am open to new technologies.

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My research interests include the following parts:

Real-time Robotics Algorithms Developing algorithms in C++ and Python for execution on edge computational platforms such as Nvidia Orin NX, focusing on real-time efficiency with limited resources.
Multi-robot System Collaboration and Intelligence Designing protocols for multi-robot systems to achieve cooperative tasks in logistics and manipulation with an emphasis on synchronization and shared objectives.
Robot Motion Planning Advancing motion planning techniques for precise navigation and task execution in cluttered environments, utilizing principles of optimization and learning for movement efficiency.
Reinforcement Learning for Robotics Implementing reinforcement learning system to enhance robots' adaptive capabilities for improved autonomy in diverse operational scenarios.
CoNi-MPC: Cooperative Non-inertial Frame Based Model Predictive Control
Baozhe Zhang*, Xinwei Chen*, Zhehan Li, Giovanni Beltrame, Chao Xu, Fei Gao, Yanjun Cao
RA-L, 2023 (accepted)
project page / video / arXiv

A novel solution for UAV control in cooperative multi-robot systems, which can be used in various scenarios such as leader-following, landing on a moving base, or specific relative motion with a target.


This is a ROS wrapper of the implementation of a pose tracking library ICG developed by DLR.


This repository contains the code about a workshop on two control libraries: ACADO and control-toolbox at Fast Lab, FIRE group. The respository contains two robot examples controlling an inverted pendulum and a quadrotor using these two libraries. A tutorial video in Chinese can be found at Bilibili.


This repository contains the contents about the docker tutorial workshop I hosted at Fast Lab, FIRE group. The slides can be found here.

Based on this repo.