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SLAM++: Highly efficient incremental SLAM
Date: 2018/4/16             Browse: 98

Speaker:     Dr. Viorela Ila, ANU

Time:          10:00—11:30, Apr 16

Location:    Room 1A-200, SIST Building

Host:          Prof. Laurent Kneip

Abstract:

The most common way to deal with the uncertainty present in noisy sensorial perception is to model the estimation problem with a probabilistic framework. Maximum likelihood estimation (MLE) is a well-known method used in many robotic and computer vision applications. Under Gaussian assumption, MLE converts to a nonlinear least squares (NLS) problem. Efficient solutions exist and they are based on iteratively solving sparse linear systems until convergence. In general, the existing solutions provide only an estimation of the mean state vector, the resulting covariance being computationally too expensive to recover. Nevertheless, in many simultaneous localization and mapping (SLAM) applications, knowing only the mean vector is not enough. Data association, obtaining reduced state representations, active decisions and next best view are only a few of the applications that require fast state covariance recovery. Furthermore, computer vision and robotic applications are in general performed online. The state is updated and recomputed at every step and its size is continuously growing. SLAM++ introduces a general framework for incremental MLE, providing efficient estimation of both mean and covariance.

Bio:

Dr. Viorela Ila received the Engineering degree in Industrial Engineering and Automation from the Technical University of Cluj-Napoca, Romania, in 2000 and the Ph.D. in Information Technologies from the University of Girona, Spain, in 2005. After the PhD studies, she joined the Robotics group at the Institut de Robótica i Informàtica Industrial, Barcelona, Spain. In 2009 she has been awarded the MICINN/FULBRIGHT post-doctoral fellowship which allowed her to join the group of Prof. Frank Dellaert at College of Computing, Georgia Tech, Atlanta US. In 2010, she joined the robotic group at LAAS-CNRS, Toulouse, France, and between 2012 and 2014, she was research scientist at Brno University of Technology in Czech Republic. Dr. Ila currently is a senior lecturer at the Australian National University, and member of the ARC Centre of Excellence for Robotic Vision.

SIST-Seminar 18020