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SLAM with SC-PHD Filters: An Underwater Vehicle Application

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5 Author(s)
Chee Sing Lee ; Comput. Vision & Robot. Group, Univ. of Girona, Girona, Spain ; Sharad Nagappa ; Narcis Palomeras ; Daniel E. Clark
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The random finite-set formulation for multiobject estimation provides a means of estimating the number of objects in cluttered environments with missed detections within a unified probabilistic framework. This methodology is now becoming the dominant mathematical framework within the sensor fusion community for developing multiple-target tracking algorithms. These techniques are also gaining traction in the field of feature-based simultaneous localization and mapping (SLAM) for mobile robotics. Here, we present one such instance of this approach with an underwater vehicle using a hierarchical multiobject estimation method for estimating both landmarks and vehicle position.

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IEEE Robotics & Automation Magazine  (Volume:21 ,  Issue: 2 )