Xiaotian Fang 方笑天

Xiaotian graduated from School of Information Science and Technology, ShanghaiTech University in July 2020, with bachlor degree in Electronic Information Engineering. At present, he worked as research assistant in MARS Lab. Besides, he has accecpted admission and planned to pursue the master degree in ECE department, University of Washington. His research interests are robotics, optimal control, and computer vision.


  • 2016.9-2020.7: B.Eng. Electronic Information Engineering, ShanghaiTech University.


  • Move Estimation for Omni-directional Cameras using Sinusoid Fitting and eFMT

    Improve performence and extend application scenarios of original Sinusoid Fitting Rotation Estimation for Omni-directional Cameras, by changing the motion calculating method from optimal flow or FMT to eFMT (extened Fourier-Mellin Transform). The target is to make this method effective in move estimation, include transform and rotation, under a multi-depths enviroment.

  • Traffic Coordination with Decentralized Optimition and Robotics Simulation

    Coordinate the vehicles in intersection and lines merge scenarios by using decentralized optimization methods. Numerical simulations are designed to verify the feasibility of algorithms. Then, we are trying to implement traffic coordination in robotics (Turtlebots) to test its feasibility in realistic scenarios.