3 accepted papers
This work proposes a semi-elastic optimizationbased LiDAR-inertial state estimation method, which balances the constraints from LiDAR, IMU and consistency according to their unique characteristics, thereby imparts appropriate elasticity for current state to be optimized to the correct value, and ens
This paper proposes a novel LiDAR-Inertial odometry (LIO), named SR-LIO, based on an error state iterated Kalman filter (ESIKF) framework. We adapt the sweep reconstruction method, which segments and reconstructs raw input sweeps from spinning LiDAR to obtain reconstructed sweeps with higher frequen…
LiDAR-inertial odometry (LIO), which fuses complementary information of a LiDAR and an Inertial Measurement Unit (IMU), is an attractive solution for state estimation. In LIO, both pose and velocity are regarded as state variables that need to be solved. However, the widely-used Iterative Closest Po…