activity
20242026
collaborators

9 papers

cs.RO2026

A Unified Neural-Aided Alignment and Calibration Method for AUVs

Guy Damari, Zeev Yampolsky, Itzik Klein

Autonomous underwater vehicles (AUVs) rely on the fusion of inertial navigation systems (INS) and Doppler velocity logs (DVL) for accurate navigation. Before deployment, this fusio…

cs.RO2026

Information-Aided DVL Calibration

Zeev Yampolsky, Itzik Klein

The Doppler velocity log (DVL) velocity measurements are critical to the accuracy of autonomous underwater vehicle (AUV) navigation solutions and, consequently, to mission success.…

cs.RO2026

AI-Aided Advancements in Autonomous Underwater Vehicle Navigation

Guy Damari, Zeev Yampolsky, Nadav Cohen +4

Autonomous underwater vehicles (AUVs) have become indispensable for deep-sea exploration, spanning critical scientific research and commercial applications. The rapid attenuation o…

cs.RO2026

Neural-Assisted in-Motion Self-Heading Alignment

Zeev Yampolsky, Felipe O. Silva, Adriano Frutuoso +1

Autonomous platforms operating in the oceans require accurate navigation to successfully complete their mission. In this regard, the initial heading estimation accuracy and the tim…

cs.RO2025

Transformer-Based Robust Underwater Inertial Navigation in Prolonged Doppler Velocity Log Outages

Zeev Yampolsky, Nadav Cohen, Itzik Klein

Autonomous underwater vehicles (AUV) have a wide variety of applications in the marine domain, including exploration, surveying, and mapping. Their navigation systems rely heavily…

cs.LG2025

On Neural Inertial Classification Networks for Pedestrian Activity Recognition

Zeev Yampolsky, Ofir Kruzel, Victoria Khalfin Fekson +1

Inertial sensors are crucial for recognizing pedestrian activity. Recent advances in deep learning have greatly improved inertial sensing performance and robustness. Different doma…