Towards Consistent Robot Navigation
Tuesday, February 18, 2014
12:00 pm - 1:00 pm
Fitzpatrick Center Schiciano Auditorium Side B
In this talk, I will describe my research efforts in understanding and improving consistency of nonlinear estimators for robot navigation. In particular, I will focus on my novel observability-based methodology and employ the extended Kalman filter (EKF)-based simultaneous localization and mapping (SLAM) in 2D as an example to illustrate our analysis and algorithms. In the sequel, I will briefly explain how this approach can be extended to a visual-inertial navigation system (VINS) in 3D, which has great potentials in practice due to today's widespread use of mobile devices with built-in inertial sensors and cameras. Nevertheless, this observabilty-based methodology can be applicable to a large class of nonlinear estimation problems in robot navigation and beyond. Lastly, I will conclude my talk by posing some interesting but challenging open problems for the future research.