Autonomous underwater vehicles (AUVs) are regularly used for deep ocean applications. Commonly, the autonomous navigation task is carried out by a fusion between two sensors: the inertial navigation system and the Doppler velocity log (DVL). The DVL operates by transmitting four acoustic beams to the sea floor, and once reflected back, the AUV velocity vector can be estimated. However, in real-life scenarios, such as an uneven seabed, sea creatures blocking the DVL's view and, roll/pitch maneuvers, the acoustic beams' reflection is resulting in a scenario known as DVL outage. Consequently, a velocity update is not available to bind the inertial solution drift. To cope with such situations, in this paper, we leverage our BeamsNet framework and propose a Set-Transformer-based BeamsNet (ST-BeamsNet) that utilizes inertial data readings and previous DVL velocity measurements to regress the current AUV velocity in case of a complete DVL outage. The proposed approach was evaluated using data from experiments held in the Mediterranean Sea with the Snapir AUV and was compared to a moving average (MA) estimator. Our ST-BeamsNet estimated the AUV velocity vector with an 8.547% speed error, which is 26% better than the MA approach.
|Title of host publication||2023 IEEE International Symposium on Underwater Technology, UT 2023|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - 2023|
|Event||2023 IEEE International Symposium on Underwater Technology, UT 2023 - Tokyo, Japan|
Duration: 6 Mar 2023 → 9 Mar 2023
|Name||2023 IEEE International Symposium on Underwater Technology, UT 2023|
|Conference||2023 IEEE International Symposium on Underwater Technology, UT 2023|
|Period||6/03/23 → 9/03/23|
Bibliographical noteFunding Information:
N.C. is supported by the Maurice Hatter Foundation and University of Haifa presidential scholarship for students on a direct Ph.D. track.
© 2023 IEEE.
- Autonomous underwater vehicle (AUV)
- Deep Learning
- Doppler velocity log (DVL)
- Inertial navigation system (INS)
ASJC Scopus subject areas
- Automotive Engineering
- Acoustics and Ultrasonics