Conceitos essenciais
The proposed method enables accurate odometry estimation for skid-steering robots in challenging environments with point cloud degeneration by tightly coupling LiDAR, IMU, and wheel odometry with online calibration of the kinematic model.
Resumo
The study presents a tightly-coupled LiDAR-IMU-wheel odometry algorithm with online calibration of the kinematic model for skid-steering robots. This is formulated as a factor graph optimization problem.
Key highlights:
- Proposed a full linear wheel odometry factor that not only serves as a motion constraint but also performs online calibration of the kinematic parameters, addressing model errors and terrain changes.
- Estimated the uncertainty of the wheel odometry online and incorporated it into the full linear wheel odometry factor to adapt to different ground surface conditions.
- Validated the method through three experiments:
- The indoor experiment showed the method is robust to severe point cloud degeneration in long corridors and changes in wheel radii.
- The outdoor experiment demonstrated accurate trajectory estimation despite rough terrain, thanks to the online uncertainty estimation.
- The third experiment showed the online calibration enables robust odometry estimation in changing terrains.
The proposed method outperformed state-of-the-art LiDAR-IMU odometry and ablation studies, demonstrating the effectiveness of the online calibration and uncertainty estimation.
Estatísticas
The robot traveled about 120 m in the indoor environment.
The robot traveled about 64 m in the outdoor environment.
The robot traveled about 144 m in the environment with transition from bricks to outdoor stone tiles, and indoor stone tiles.
Citações
"Tunnels and long corridors are challenging environments for mobile robots because a LiDAR point cloud should degenerate in these environments."
"Despite the dynamically changing kinematic model (e.g., wheel radii changes caused by tire pressures) and terrain conditions, our method can address the model error via online calibration."
"Our method enables an accurate localization in cases of degenerated environments, such as long and straight corridors, by calibration while the LiDAR-IMU fusion sufficiently operates."