Name
Title | ||
|---|---|---|
Underwater Robot Pose Estimation Using Acoustic Methods and Intermittent Position Measurements at the Surface |
Abstract | ||
|---|---|---|
Global positioning systems can provide sufficient positioning accuracy for large scale robotic tasks in open environments. However, in underwater environments, these systems cannot be directly used, and measuring the position of underwater robots becomes more difficult. In this paper we first evaluate the performance of existing pose estimation techniques for an underwater robot equipped with commonly used sensors for underwater control and pose estimation, in a simulated environment. In our case these sensors are inertial measurement units, Doppler velocity log sensors, and ultra-short baseline sensors. Secondly, for situations in which underwater estimation suffers from drift, we investigate the benefit of intermittently correcting the position using a high-precision surface-based sensor, such as regular GPS or an assisting unmanned aerial vehicle that tracks the underwater robot from above using a camera. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/AQTR55203.2022.9802002 | 2022 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR) |
Keywords | DocType | ISBN |
Pose estimation,Extended Kalman Filter,underwater robotics,Robot Operating System | Conference | 978-1-6654-7934-9 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vicu-Mihalis Maer | 1 | 0 | 0.34 |
| Levente Tamás | 2 | 0 | 0.34 |
| Lucian Busoniu | 3 | 0 | 1.35 |