© 2015 IEEE. SLAM (Simultaneous Localization and Mapping) for underwater vehicles is a challenging research topic due to the limitations of underwater localization sensors and error accumulation over long-term operations. Furthermore, acoustic sensors for mapping often provide noisy and distorted images or low-resolution ranging, while video images provide highly detailed images but are often limited due to turbidity and lighting. This paper presents a review of the approaches used in state-of-the-art SLAM techniques: Extended Kalman Filter SLAM (EKF-SLAM), FastSLAM, GraphSLAM and its application in underwater environments.
|Original language||American English|
|Number of pages||6|
|State||Published - 1 Jan 2015|
|Event||ICARA 2015 - Proceedings of the 2015 6th International Conference on Automation, Robotics and Applications - |
Duration: 1 Jan 2015 → …
|Conference||ICARA 2015 - Proceedings of the 2015 6th International Conference on Automation, Robotics and Applications|
|Period||1/01/15 → …|