Spatiotemporal Calibration of Doppler Velocity Logs for Underwater Robots
Zhao, Hongxu, Zeng, Guangyang, Shao, Yunling, Zhang, Tengfei, Wu, Junfeng
–arXiv.org Artificial Intelligence
Acoustic sensors, particularly Doppler V elocity Logs (DVLs), have become indispensable for underwater navigation and environmental sensing. To enable robust fusion of DVL measurements with data from other sensors, precise calibration of extrinsic parameters and temporal synchronization is critical, especially in challenging underwater operating conditions [1]-[5]. Prior work by Xu et al. [6] and Westman and Kaes [7] framed the DVL-camera calibration as an odometry alignment problem, matching the trajectory from a DVL-IMU system against the visual one from a camera. A critical limitation of these approaches is their implicit assumption of known and static DVL-IMU extrinsics, which is frequently violated in underwater environments due to their dynamic nature. While studies in [8]-[11] address the calibration of IMU-free DVLs, their applicability is strictly limited to co-sensors that provide direct linear and angular velocity measurements, such as SINS/GPS systems. Crucially, a significant gap persists across all these works: none address the calibration of translational extrinsic nor account for temporal synchronization across heterogeneous sensors.
arXiv.org Artificial Intelligence
Oct-29-2025
- Country:
- Asia > China
- Guangdong Province > Shenzhen (0.04)
- Hong Kong (0.04)
- North America > United States
- Massachusetts > Middlesex County > Cambridge (0.04)
- Asia > China
- Genre:
- Research Report (0.82)
- Technology:
- Information Technology > Artificial Intelligence
- Machine Learning (0.68)
- Representation & Reasoning > Optimization (0.68)
- Robots (0.87)
- Information Technology > Artificial Intelligence