Our Lab


Welcome to the website of FAST (Field Autonomous System & compuTing) Lab led by Prof. Chao Xu and Prof. Fei Gao. Our Lab is part of the Control System & Cybernetics (CSC) Institute at Zhejiang University.

Our group is mainly engaged in the following fields:

• Autonomous Systems (navigation, control, motion planning, perception, SLAM, etc.);

• AI (imaging, vision, machine learning, control, etc.) for Turbulent Flows;

• Data-driven Science and Engineering;

• Synergy of AI and Control.

Code for AM-Traj is now available on GitHub


AM-Traj is a C++11 header-only library for generating large-scale piecewise polynomial trajectories for aggressive autonomous flights, with highlights on its superior computational efficiency and simultaneous spatial-temporal optimality. Besides, an extremely fast feasibility checker is designed for various kinds of constraints. All components in this framework leverage the algebraic convenience of the polynomial trajectory optimization problem, thus our method is capable of computing a spatial-temporal optimal trajectory with 60 pieces within 5ms, i.e., 150Hz at least. You just need to include “am_traj.hpp” and “root_finder.hpp” in your code. Please use the up-to-date master branch which may have a better performance than the one in our paper.

Author: Zhepei Wang and Fei Gao from the ZJU Fast Lab.

Related Papers:

Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight, Zhepei Wang, Xin Zhou, Chao Xu, Jian Chu, and Fei Gao, submitted to RA-L/IROS 2020.

Detailed Proofs of Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight, Zhepei Wang, Xin Zhou, Chao Xu, and Fei Gao, the supplementary material.

Video Linksyoutube or bilibili

 


Postdoc Opportunities at the FAST Lab, Zhejiang University


ZJU was founded in 1897, which is one of the oldest and most prestigious institutions of higher education in China. It is considered a top university in the Chinese mainland, which is ranked #6 in Asia and #54 worldwide according to the QS University Rankings for 2020.

The FAST Lab is the recipients of the Champion of the International Aerial Robotics Competition (2018), the First Prize of the DJI RoboMaster AI Global Challenges (2019), as well as the Champion of the World Robotic Sailing Competition (2019). The FACT Lab has a close collaborative relationship with industrial companies such as the Supcon and the DJI, etc. For more information about the FAST Lab, please visit www.kivact.com.

The FAST Lab is calling for applications for several postdoc positions in the areas of unmanned systems (e.g., mechatronic control, autonomous navigation & planning) and industrial intelligence (e.g., industrial vision systems, machine learning and control systems).

Successful applicants should hold a Ph.D. in the areas of engineering or science disciplines, such as control science & engineering, robotics, applied math, computing, electrical engineering, electronics, mechanical & aerospace engineering, but not limited to these.

Application packages should send a CV and sample publications to wuwenjuan@zju.edu.cn entitled by “FAST Postdoc Application”. Positions remain open until filled. If you have any questions regarding the postdoc positions, please do not hesitate to contact cxu@zju.edu.cn (Chao Xu) and fgaoaa@zju.edu.cn (Fei Gao).

The Chinese version is available on this page.