Profile
Fan is a postgraduate research student in the Department of Informatics at King’s College London under the supervision of Dr Matthew Howard and Dr Daniele Magazzeni.
He obtained his MSc in Financial Mathematics at King's. Before that, he completed BSc in Mathematics at University of Science and Technology Beijing.
Research Project
He is interested in the application of machine learning into the area of robot control. More specifically the interests span topics in variable impedance actuators (VIA), nonparametric statistical learning, optimal control, stochastic optimal control and reinforcement learning.
Project Update
Fan currently focus on optimal control of robots with variable impedance taking account of energy efficiency and uncertainties. He is interested in the problem of how to use largescale dataset collected during operation to adapt prediction model and optimal movements. Recently, various research efforts have been made to exploit the advantages of variable impedance actuators (VIA). It has been shown that task performance in dynamical movements can be improved by exploiting the energy storage capability of robotic systems incorporating physical elastic components such as springs. His research focuses on how to achieve energy efficient movements of VIAs by utilizing the inherent redundancy introduced by variable impedance design.
Funding Awards
- Sir Professor Richard Trainor scholarship
Contact
Department of Informatics
Strand Campus
King's College London, Strand,
London, WC2R 2LS
United Kingdom
Email: Fan[dot]wu@kcl.ac.uk
Personal Blog: wudf.wordpress.com