Chengwei Zhao — accepted AI-conference papers

2025

Semi-Elastic LiDAR-Inertial Odometry

Zikang Yuan, Fengtian Lang, Tianle Xu, Ruiye Ming, Chengwei Zhao, Xin Yang

ICRA 2025

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

Cited by 12 Source ↗code ↗Scholar ↗

2024

I2EKF-LO: A Dual-Iteration Extended Kalman Filter Based LiDAR Odometry

Wenlu Yu, Jie Xu, Chengwei Zhao, Lijun Zhao, Thien-Minh Nguyen, Shenghai Yuan +2

IROS 2024poster

LiDAR odometry is a pivotal technology in the fields of autonomous driving and autonomous mobile robotics. However, most of the current works focus on nonlinear optimization methods, and still existing many challenges in using the traditional Iterative Extended Kalman Filter (IEKF) framework to tack…

Cited by 10 Source ↗code ↗Scholar ↗