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ICARCV
2006
IEEE

Simultaneous Localization and Mapping with Stereo Vision

10 years 4 months ago
Simultaneous Localization and Mapping with Stereo Vision
— In the simultaneous localization and mapping (SLAM) problem, a mobile robot must build a map of its environment while simultaneously determining its location within that map. We propose a new algorithm, for visual SLAM (VSLAM), in which the robot’s only sensory information is video imagery. Our approach combines stereo vision with a popular sequential Monte Carlo (SMC) algorithm, the Rao-Blackwellised particle filter, to simultaneously explore multiple hypotheses about the robot’s six degree-of-freedom trajectory through space and maintain a distinct stochastic map for each of those candidate trajectories. We demonstrate the algorithm’s effectiveness in mapping a large outdoor virtual reality environment in the presence of odometry error. Keywords—Localization, mapping, stereo vision, RaoBlackwellised particle filter, visual landmarks
Matthew N. Dailey, Manukid Parnichkun
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where ICARCV
Authors Matthew N. Dailey, Manukid Parnichkun
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