Visual Pitch and Roll Estimation For Inland Water Vessels
- Motion estimation is an essential element for autonomous vessels. It is used e.g. for lidar motion compensation as well as mapping and detection tasks in a maritime environment. Because the use of gyroscopes is not reliable and a high performance inertial measurement unit is quite expensive, we present an approach for visual pitch and roll estimation that utilizes a convolutional neural network for water segmentation, a stereo system for reconstruction and simple geometry to estimate pitch and roll. The algorithm is validated on a novel, publicly available dataset recorded at Lake Constance. Our experiments show that the pitch and roll estimator provides accurate results in comparison to an Xsens IMU sensor. We can further improve the pitch and roll estimation by sensor fusion with a gyroscope. The algorithm is available in its implementation as a ROS node.
| Author: | Dennis Griesser, Georg UmlaufORCiDGND, Matthias O. FranzORCiDGND |
|---|---|
| DOI: | https://doi.org/10.1109/ICRA48891.2023.10160460 |
| ISBN: | 979-8-3503-2365-8 |
| ISBN: | 979-8-3503-2366-5 |
| Parent Title (English): | 40th IEEE International Conference on Robotics and Automation (ICRA 2023), 29 May 2023 - 02 June 2023, London, UK |
| Volume: | 2023 |
| Publisher: | IEEE |
| Document Type: | Conference Proceeding |
| Language: | English |
| Year of Publication: | 2023 |
| Release Date: | 2023/07/24 |
| Tag: | Segmentation; Reconstruction; Sensor fusion |
| First Page: | 1961 |
| Last Page: | 1967 |
| Note: | Volltext im Campusnetz der Hochschule Konstanz via Datenbank IEEE Xplore abrufbar. |
| Institutes: | Institut für Optische Systeme - IOS |
| Relevance: | Peer reviewed nach anderen Listungen (mit Nachweis zum Peer Review Verfahren) |
| Open Access?: | Nein |
| Licence (German): |  Urheberrechtlich geschützt |
