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Vision-based estimation of three-dimensional position and pose of multiple underwater vehicles

8 years 12 months ago
Vision-based estimation of three-dimensional position and pose of multiple underwater vehicles
— This paper describes a model-based probabilistic framework for tracking a fleet of laboratory-scale underwater vehicles using multiple fixed cameras. We model the target motion as a steered particle whose dynamics evolve on the special Euclidean group. We provide a likelihood function that extracts three-dimensional position and pose measurements from monocular images using projective geometry. The tracking algorithm uses particle filtering with selective resampling based on a threshold and nearest neighbor data association for multiple targets. We describe results obtained from two tracking experiments: first with one vehicle and a second experiment with two targets. The tracking algorithm for single target experiment is validated using data denial.
Sachit Butail, Derek A. Paley
Added 24 May 2010
Updated 24 May 2010
Type Conference
Year 2009
Where IROS
Authors Sachit Butail, Derek A. Paley
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