ALIVE-LIO reduces pose drift in degenerate LiDAR environments by selectively fusing a neural network's inertial velocity prediction into an ESKF only when LiDAR observability is lost.
R3LIVE: A robust, real-time, RGB-colored, LiDAR-inertial-visual tightly-coupled state estimation and mapping pack- age
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ALIVE-LIO: Degeneracy-Aware Learning of Inertial Velocity for Enhancing ESKF-Based LiDAR-Inertial Odometry
ALIVE-LIO reduces pose drift in degenerate LiDAR environments by selectively fusing a neural network's inertial velocity prediction into an ESKF only when LiDAR observability is lost.