Interactive & Emergent Autonomy Lab

Taosha Fan


My research lies at the intersection of robotic control, simulation and estimation. I try to develop efficient and guaranteed algorithms for general robotic problems using a combination of optimization, differential geometry and probability theory.


Control for Nonlinear and Hybrid Systems


M.S.E. Mechanical Engineering, Johns Hopkins University, 2015
M.A. Mathematics, Johns Hopkins University, 2015
B.S. Automotive Engineering, Tongji University, 2013

Other Interests

I'm a fan of swimming and hiking.


Generalized proximal methods for pose graph optimization
T. Fan and T. D. Murphey
International Symposium on Robotics Research (ISRR), 2019.

CPL-Sync: Efficient and guaranteed planar pose graph optimization using the complex number representation
T. Fan, H. Wang, M. Rubenstein, and T. D. Murphey
IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2019. Winner of ABB Best Student Paper Award. PDF

Efficient computation of higher-order variational integrators in robotic simulation and trajectory optimization
T. Fan, J. Schultz, and T. D. Murphey
Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018. PDF, Appendix, Video

Decentralized and recursive identification for cooperative manipulation of unknown rigid body with local measurements
T. Fan, H. Weng, and T. D. Murphey
IEEE Int. Conf. on Decision and Control (CDC), pp. 2842–2849, 2017. PDF

Online feedback control for input-saturated robotic systems on Lie groups
T. Fan and T. D. Murphey
Robotics: Science and Systems Proceedings, 2016. PDF

Structured linearization of discrete mechanical systems on Lie groups: a synthesis of analysis and control
T. Fan and T. D. Murphey
IEEE Int. Conf. on Decision and Control (CDC), pp. 1092 – 1099, 2015. PDF