Dr. Guoquan Huang
Department of Mechanical Engineering
University of Delaware
208 Spencer Lab
Newark, DE 19716
Dr. Huang is an Assistant Professor in Mechanical Engineering at the University of Delaware. Prior to UD, he was a Postdoctoral Associate with the Marine Robotics Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT). He received the B.Eng. degree in automation (electrical engineering) from the University of Science and Technology, Beijing, China, in 2002, and the M.Sc. and Ph.D. degrees in computer science (robotics) from the University of Minnesota, Twin Cities, in 2009 and 2012, respectively. From 2003 to 2005, he was a Research Assistant with the Department of Electrical Engineering, Hong Kong Polytechnic University, Hong Kong. His research interests include robotics, computer vision and robot learning, with special emphasis on probabilistic perception, estimation, and control of autonomous ground, aerial, and underwater vehicles.
Y. Latif, G. Huang, J. Leonard, and J. Neira, “An Online Sparsity-Cognizant Loop-Closure Algorithm for Visual Navigation”, In Proc. Robotics: Science and Systems Conference (RSS), Berkeley, CA, July 12 – 16, 2014.
G. Huang, M. Kaess, and J. Leonard, “Towards Consistent Visual-Inertial Navigation”, In Proc. IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, May 31 - June 5, 2014.
G. Huang, A.I. Mourikis, and S.I. Roumeliotis, "A Quadratic-Complexity Observability-Constrained Unscented Kalman Filter for SLAM", IEEE Transactions on Robotics (TRO), Vol. 29, No. 5, Oct 2013, pp. 1226-1243.
G. Huang, N. Trawny, A.I. Mourikis, and S.I. Roumeliotis. "Observability-based Consistent EKF Estimators for Multi-robot Cooperative Localization", Autonomous Robots (AURO), Vol. 30, No. 1, 2011, pp. 99-122.
G. Huang, A.I. Mourikis, and S.I. Roumeliotis, "Observability-based Rules for Designing Consistent EKF SLAM Estimators", International Journal of Robotics Research (IJRR), Vol. 29, No. 5, 2010, pp. 502-528.
Robotics & Controls
Probabilistic perception, estimation and control of robotic systems; robot localization and mapping; aided inertial navigation; target tracking; convex optimization; probabilistic graphical models
Dynamics & Control Theory
Nonlinear estimation and control
Inertial navigation system