4 papers · 1 filter
Uncertainty-Aware Velocity Correction for Proprioceptive Vehicle Localization using Evidential Mamba
Abinav Kalyanasundaram, Karthikeyan Chandra Sekaran, Wolfgang Utschick +1
Reliable localization in GNSS-denied environments remains a fundamental challenge for intelligent vehicles, as inertial navigation systems accumulate unbounded drift without extern…
Physics-Regularized Machine Learning for Proprioceptive Vehicle Localization Using Onboard Sensors
Abinav Kalyanasundaram, Karthikeyan Chandra Sekaran, Wolfgang Utschick +1
Accurate and robust localization is essential for autonomous mobility systems in real-world environments. While fusing Inertial Measurement Unit (IMU) data with satellite-based cor…
Hybrid Machine Learning Model with a Constrained Action Space for Trajectory Prediction
Alexander Fertig, Lakshman Balasubramanian, Michael Botsch
Trajectory prediction is crucial to advance autonomous driving, improving safety, and efficiency. Although end-to-end models based on deep learning have great potential, they often…
Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation
Abinav Kalyanasundaram, Karthikeyan Chandra Sekaran, Philipp Stauber +3
Precise vehicle state estimation is crucial for safe and reliable autonomous driving. The number of measurable states and their precision offered by the onboard vehicle sensor syst…