A performance analysis of omnidirectional vision based simultaneous localization and mapping
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Date
2012
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info:eu-repo/semantics/closedAccess
Abstract
This paper presents a performance analysis of omnidirectional vision based Simultaneous Localization and Mapping (SLAM). In omnidirectional vision based SLAM; robots perform vision based SLAM using only monocular omnidirectional cameras. In this paper, we mainly investigate the use of an omnidirectional camera for Extended Kalman Filter (EKF) based SLAM. To evaluate the success of omnidirectional vision based SLAM, we have also conducted the same simulations using a laser range finder (LRF). Main contributions of this paper are the use of an omnidirectional camera to perform SLAM in the Unified System for Automation and Robot Simulation (USARSim) environment, which is controlled by MATLAB in our study. The results of USARSim simulations show that depending on the environmental conditions omnidirectional cameras can be used as an alternative to other range bearing sensors and stereo cameras. © 2012 Springer-Verlag.
Description
IEEE Computational Intelligence Society;International Neural Network Society;National Science Foundation of China
8th International Conference on Intelligent Computing Technology, ICIC 2012 -- 25 July 2012 through 29 July 2012 -- Huangshan -- 92041
8th International Conference on Intelligent Computing Technology, ICIC 2012 -- 25 July 2012 through 29 July 2012 -- Huangshan -- 92041
Keywords
Matlab; Omnidirectional Camera; Slam; Usarsim, Environmental Conditions; Laser Range Finders; Omni-Directional Vision; Omnidirectional Cameras; Performance Analysis; Robot Simulations; Slam; Stereo Cameras; Unified System; Usarsim; Vision Based Slam; Computer Vision; Intelligent Computing; Mathematical Techniques; Matlab; Video Cameras; Robotics
Journal or Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
WoS Q Value
Scopus Q Value
Q3
Volume
7389 LNCS
