LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

© 2020 IEEE. We propose a framework for tightly-coupled lidar inertial odometry via smoothing and mapping, LIO-SAM, that achieves highly accurate, real-time mobile robot trajectory estimation and map-building. LIO-SAM formulates lidar-inertial odometry atop a factor graph, allowing a multitude of re...

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Bibliographic Details
Main Authors: Shan, Tixiao, Englot, Brendan, Meyers, Drew, Wang, Wei, Ratti, Carlo, Rus, Daniela
Other Authors: Massachusetts Institute of Technology. Department of Urban Studies and Planning
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2022
Online Access:https://hdl.handle.net/1721.1/144041

Internet

https://hdl.handle.net/1721.1/144041

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