98 citations · 349 across the 25 of their papers we have counts for
25 papers
GHNet:Learning GNSS Heading from Velocity Measurements
Nitzan Dahan, Itzik Klein
By utilizing global navigation satellite system (GNSS) position and velocity measurements, the fusion between the GNSS and the inertial navigation system provides accurate and robu…
Leveraging Past DVL Velocity Measurements for Acceleration-Aided AUV Navigation
Nadav Cohen, Orzion Levy, Itzik Klein
Autonomous underwater vehicles (AUVs) commonly rely on the fusion of an inertial navigation system (INS) with a Doppler velocity log (DVL) through a nonlinear filter to maintain ac…
VIO-DualProNet: Visual-Inertial Odometry with Learning Based Process Noise Covariance
Dan Solodar, Itzik Klein
Visual-inertial odometry (VIO) is a vital technique used in robotics, augmented reality, and autonomous vehicles. It combines visual and inertial measurements to accurately estimat…
Parametric and State Estimation of Stationary MEMS-IMUs: A Tutorial
Daniel Engelsman, Yair Stolero, Itzik Klein
Inertial navigation systems (INS) are widely used in almost any operational environment, including aviation, marine, and land vehicles. Inertial measurements from accelerometers an…
Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions
Nadav Cohen, Itzik Klein
Inertial sensing is used in many applications and platforms, ranging from day-to-day devices such as smartphones to very complex ones such as autonomous vehicles. In recent years,…
MissBeamNet: Learning Missing Doppler Velocity Log Beam Measurements
Mor Yona, Itzik Klein
One of the primary means of sea exploration is autonomous underwater vehicles (AUVs). To perform these tasks, AUVs must navigate the rough challenging sea environment. AUVs usually…
Set-Transformer BeamsNet for AUV Velocity Forecasting in Complete DVL Outage Scenarios
Nadav Cohen, Zeev Yampolsky, Itzik Klein
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 i…
ProNet: Adaptive Process Noise Estimation for INS/DVL Fusion
Barak Or, Itzik Klein
Inertial and Doppler velocity log sensors are commonly used to provide the navigation solution for autonomous underwater vehicles (AUV). To this end, a nonlinear filter is adopted…
LiBeamsNet: AUV Velocity Vector Estimation in Situations of Limited DVL Beam Measurements
Nadav Cohen, Itzik Klein
Autonomous underwater vehicles (AUVs) are employed for marine applications and can operate in deep underwater environments beyond human reach. A standard solution for the autonomou…
Outlier-Insensitive Kalman Filtering Using NUV Priors
Shunit Truzman, Guy Revach, Nir Shlezinger +1
The Kalman filter (KF) is a widely-used algorithm for tracking the latent state of a dynamical system from noisy observations. For systems that are well-described by linear Gaussia…
A Learning-based approach for bias elimination in low cost gyroscopes
Daniel Engelsman, Itzik Klein
Modern sensors play a pivotal role in many operating platforms, as they manage to track the platform dynamics at a relatively low manufacturing costs. Their widespread use can be f…
A Hybrid Adaptive Velocity Aided Navigation Filter with Application to INS/DVL Fusion
Barak Or, Itzik Klein
Autonomous underwater vehicles (AUV) are commonly used in many underwater applications. Usually, inertial sensors and Doppler velocity log readings are used in a nonlinear filter t…
Self-Supervised Monocular Depth Underwater
Shlomi Amitai, Itzik Klein, Tali Treibitz
Depth estimation is critical for any robotic system. In the past years estimation of depth from monocular images have shown great improvement, however, in the underwater environmen…
Data-Driven Meets Navigation: Concepts, Models, and Experimental Validation
Itzik Klein
The purpose of navigation is to determine the position, velocity, and orientation of manned and autonomous platforms, humans, and animals. Obtaining accurate navigation commonly re…
A Unified Filter for Fusion of Multiple Inertial Measurement Units
Yaakov Libero, Itzik Klein
Navigation plays a vital role in the ability of autonomous surface and underwater platforms to complete their tasks. Most navigation systems apply a fusion between inertial sensors…
AG2U -- Autonomous Grading Under Uncertainties
Yakov Miron, Yuval Goldfracht, Chana Ross +2
Surface grading, the process of leveling an uneven area containing pre-dumped sand piles, is an important task in the construction site pipeline. This labour-intensive process is o…
MoRPI: Mobile Robot Pure Inertial Navigation
Aviad Etzion, Itzik Klein
Mobile robots are used in industrial, leisure, and military applications. In some situations, a robot navigation solution relies only on inertial sensors and as a consequence, the…
A Hybrid Model and Learning-Based Adaptive Navigation Filter
Barak Or, Itzik Klein
The fusion between an inertial navigation system and global navigation satellite systems is regularly used in many platforms such as drones, land vehicles, and marine vessels. The…
BeamsNet: A data-driven Approach Enhancing Doppler Velocity Log Measurements for Autonomous Underwater Vehicle Navigation
Nadav Cohen, Itzik Klein
Autonomous underwater vehicles (AUV) perform various applications such as seafloor mapping and underwater structure health monitoring. Commonly, an inertial navigation system aided…
Adaptive Step Size Learning with Applications to Velocity Aided Inertial Navigation System
Barak Or, Itzik Klein
Autonomous underwater vehicles (AUV) are commonly used in many underwater applications. Recently, the usage of multi-rotor unmanned autonomous vehicles (UAV) for marine application…
Adaptive Attitude Estimation Using a Hybrid Model-Learning Approach
Eran Vertzberger, Itzik Klein
Attitude determination using the smartphone's inertial sensors poses a major challenge due to the sensor low-performance grade and variate nature of the walking pedestrian. In this…
Data-Driven Denoising of Stationary Accelerometer Signals
Daniel Engelsman, Itzik Klein
Modern navigation solutions are largely dependent on the performances of the standalone inertial sensors, especially at times when no external sources are available. During these o…
Learning Vehicle Trajectory Uncertainty
Barak Or, Itzik Klein
A novel approach for vehicle tracking using a hybrid adaptive Kalman filter is proposed. The filter utilizes recurrent neural networks to learn the vehicle's geometrical and kinema…
Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space Models
Itzik Klein, Guy Revach, Nir Shlezinger +3
Providing a metric of uncertainty alongside a state estimate is often crucial when tracking a dynamical system. Classic state estimators, such as the Kalman filter (KF), provide a…