LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Tixiao Shan,Brendan Englot,Drew Meyers,Wei Wang,Carlo Ratti,Daniela Rus,Tixiao Shan,Brendan Englot,Drew Meyers,Wei Wang,Carlo Ratti,Daniela Rus
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 relative and absolute measurements, including loop closures, to be incorporated from different sources as factors i...
