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NAViLoss: An Underwater Navigation-Aware Dual-Residual Objective for Physics-Consistent Learning
Arup Kumar Sahoo, Itzik Klein
Autonomous underwater vehicles (AUVs) commonly rely on inertial navigation systems (INS) aided by Doppler velocity logs (DVLs) for reliable underwater navigation. Accurate DVL velo…
DVL-DeepONet: A Physics-Guided Operator Learning for Resilient Underwater Navigation
Arup Kumar Sahoo, Itzik Klein
Autonomous Underwater Vehicles (AUVs) rely heavily on the fusion of inertial sensors and Doppler velocity logs (DVLs) for navigation. In standard autonomous navigation systems, the…
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…
PiDR: Physics-Informed Inertial Dead Reckoning for Autonomous Platforms
Arup Kumar Sahoo, Itzik Klein
A fundamental requirement for full autonomy is the ability to sustain accurate navigation in the absence of external data, such as GNSS signals or visual information. In these chal…
MoRPI-PINN: A Physics-Informed Framework for Mobile Robot Pure Inertial Navigation
Arup Kumar Sahoo, Itzik Klein
A fundamental requirement for full autonomy in mobile robots is accurate navigation even in situations where satellite navigation or cameras are unavailable. In such practical situ…