Title :
The vSLAM Algorithm for Robust Localization and Mapping
Author :
Karlsson, Niklas ; Di Bernardo, Enrico ; Ostrowski, Jim ; Goncalves, Luis ; Pirjanian, Paolo ; Munich, Mario E.
Author_Institution :
Evolution Robotics, Inc. Pasadena, California, USA Email: niklas@evolution.com
Abstract :
This paper presents the Visual Simultaneous Localization and Mapping (vSLAMTM) algorithm, a novel algorithm for simultaneous localization and mapping (SLAM). The algorithm is vision-and odometry-based, and enables low-cost navigation in cluttered and populated environments. No initial map is required, and it satisfactorily handles dynamic changes in the environment, for example, lighting changes, moving objects and/or people. Typically, vSLAM recovers quickly from dramatic disturbances, such as “kidnapping”.
Keywords :
Kalman filter; Mixed proposal distribution; Particle filter; SLAM; vision; Cameras; Computer vision; Mobile robots; Navigation; Particle filters; Proposals; Robot sensing systems; Robot vision systems; Robustness; Simultaneous localization and mapping; Kalman filter; Mixed proposal distribution; Particle filter; SLAM; vision;
Conference_Titel :
Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on
Print_ISBN :
0-7803-8914-X
DOI :
10.1109/ROBOT.2005.1570091