Lab Meeting October 17th, 2013 (Jeff): Temporally Scalable Visual SLAM using a Reduced Pose Graph

Title: Temporally Scalable Visual SLAM using a Reduced Pose Graph

Authors: Hordur Johannsson, Michael Kaess, Maurice Fallon, and John J. Leonard

Abstract:

In this paper, we demonstrate a system for temporally scalable visual SLAM using a reduced pose graph representation. Unlike previous visual SLAM approaches that maintain static keyframes, our approach uses new measurements to continually improve the map, yet achieves efficiency by avoiding adding redundant frames and not using marginalization to reduce the graph. To evaluate our approach, we present results using an online binocular visual SLAM system that uses place recognition for both robustness and multi-session operation. Additionally, to enable large-scale indoor mapping, our system automatically detects elevator rides based on accelerometer data. We demonstrate long-term mapping in a large multi-floor building, using approximately nine hours of data collected over the course of six months. Our results illustrate the capability of our visual SLAM system to map a large are over extended period of time.


IEEE International Conference on Robotics and Automation (ICRA), 2013

Link:
LocalLink
http://people.csail.mit.edu/kaess/pub/Johannsson13icra.pdf

Reference Link:
Another paper with the same title:
In RSS Workshop on Long-term Operation of Autonomous Robotic Systems in Changing Environments, 2012.
http://people.csail.mit.edu/kaess/pub/Johannsson12rssw.pdf