9 papers
BLENDS: Bayesian Learning-Enhanced Deep Smoothing for GNSS-Denied Environments
Nadav Cohen, Itzik Klein
Maintaining accurate navigation during GNSS outages remains a significant challenge for autonomous systems relying on low-cost inertial sensors. While classical smoothing methods,…
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…
Bayesian Learning-Enhanced Navigation with Deep Smoothing for Inertial-Aided Navigation
Nadav Cohen, Itzik Klein
Accurate post-processing navigation is essential for applications such as survey and mapping, where the full measurement history can be exploited to refine past state estimates. Fi…
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…
Enhancing Underwater Navigation through Cross-Correlation-Aware Deep INS/DVL Fusion
Nadav Cohen, Itzik Klein
The accurate navigation of autonomous underwater vehicles critically depends on the precision of Doppler velocity log (DVL) velocity measurements. Recent advancements in deep learn…
Performance Analysis of Spatial and Temporal Learning Networks in the Presence of DVL Noise
Rajini Makam, Nadav Cohen, Sumukh Shadakshari +3
Navigation is a critical aspect of autonomous underwater vehicles (AUVs) operating in complex underwater environments. Since global navigation satellite system (GNSS) signals are u…