Random finite sets for robot mapping and SLAM. New concepts in autonomous robotic map representations.

DOI10.1007/978-3-642-21390-8zbMath1231.68017OpenAlexW151959536MaRDI QIDQ2275354

Ba-Ngu Vo, Martin Adams, John Mullane, Ba Tuong Vo

Publication date: 8 August 2011

Published in: Springer Tracts in Advanced Robotics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-21390-8

zbMATH Keywords

uncertaintyautonomous navigationautonomous vehiclerandom finite setsfeature based robotic mapping (FBRM)Kalman Gaussian mixture implementationprobability hypothesis density (PHD)simultaneous localization and map building (SLAM)surroundings

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Geometric probability and stochastic geometry (60D05) Bayesian inference (62F15) Applications of statistics in engineering and industry; control charts (62P30) Automated systems (robots, etc.) in control theory (93C85) Research exposition (monographs, survey articles) pertaining to systems and control theory (93-02) Research exposition (monographs, survey articles) pertaining to computer science (68-02) Artificial intelligence for robotics (68T40)

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Distributed multiagent control approach for multitarget tracking ⋮ An ant-based filtering random-finite-set approach to simultaneous localization and mapping ⋮ Uncertainty modelling and computational aspects of data association

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