😎 A current list of LiDAR-IMU calibration method
LiDAR and IMU are among the widely used sensors in the field of self-driving cars and robotics. To fuse both sensors and use them for algorithms (such as LiDAR-inertial SLAM), it is essential to obtain the exact extrinsic parameter.
Inspired by Deephome/Awesome-LiDAR-Camera-Calibration, this repository summarizes the LiDAR-IMU calibration methods currently being studied in research fields and related toolboxes.
Target means calibration target.
"S" means spatial information (Transformation matrix) and "T" means temporal information (time offset).
| Paper | Published | Target | Key words | Code |
|---|---|---|---|---|
| 3D Lidar-IMU Calibration Based on Upsampled Preintegrated Measurements for Motion Distortion Correction | ICRA 2018 | S+T | IMU Preintegration, Plane association | - |
| Error modeling and extrinsic–intrinsic calibration for LiDAR-IMU system based on cone-cylinder features | RAS 2019 | S | Cone-cylinder features, IMU intrinsic parameter, EKF based | - |
| Targetless Calibration of LiDAR-IMU System Based on Continuous-time Batch Estimation | IROS 2020 | S+T | Continous time trajectory, Surfel map | LI-Calib |
| A Novel Multifeature Based On-Site Calibration Method for LiDAR-IMU System | TIE 2020 | S | Multi-type geometric features, Cone-cylinder features(RAS 2019) extended version | - |
| Motion-based Calibration between Multiple LiDARs and INS with Rigid Body Constraint on Vehicle Platform | IV 2020 | S | Graph structure-based optimization, Multiple LiDAR | - |
| Efficient Multi-sensor Aided Inertial Navigation with Online Calibration | ICRA 2021 | S+T | MSCKF based, Multi-sensor INS, | - |
| Target-free Extrinsic Calibration of a 3D-Lidar and an IMU | MFI 2021 | S | EKF based | imu_lidar_calibration |
| 3D LiDAR/IMU Calibration Based on Continuous-Time Trajectory Estimation in Structured Environments | IEEE Access 2021 | S | Continuous-Time Trajectory, Gaussian process(GP) regression | - |
| Observability-Aware Intrinsic and Extrinsic Calibration of LiDAR-IMU Systems | TRO 2022 | S+T | LI-Calib(IROS 2020) extension version | OA-LICalib |
| Robust Real-time LiDAR-inertial Initialization | IROS 2022 | S+T | IESKF based, FAST-LIO initialization | LI-Init |
| An Extrinsic Calibration Method of a 3D-LiDAR and a Pose Sensor for Autonomous Driving | Arxiv 2022 | S | LiDAR-INS calibration part of OpenCalib | LiDAR2INS |
| AFLI-Calib: Robust LiDAR-IMU extrinsic self-calibration based on adaptive frame length LiDAR odometry | ISPRS 2023 | S | Continuous-time model, Optimization based | - |
| GRIL-Calib: Targetless Ground Robot IMU-LiDAR Extrinsic Calibration Method using Ground Plane Motion Constraints | RAL 2024 | S+T | LiDAR-IMU calibration for ground robot | GRIL-Calib |
| ToolBox | Keywords |
|---|---|
| OpenCalib(SensorsCalibration) | Calibration Toolbox for Autonomous Driving |
| chennuo0125-HIT/lidar_imu_calib | Only calculate extrinsic rotation parameter |
| ethz-asl/lidar_align | Accurate results require highly non-planar motions |
If you have any question, feel free to leave an issue or send an email. 😄
