5 papers
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…
Online Monitoring Framework for Automotive Time Series Data using JEPA Embeddings
Alexander Fertig, Karthikeyan Chandra Sekaran, Lakshman Balasubramanian +1
As autonomous vehicles are rolled out, measures must be taken to ensure their safe operation. In order to supervise a system that is already in operation, monitoring frameworks are…
UrbanIng-V2X: A Large-Scale Multi-Vehicle, Multi-Infrastructure Dataset Across Multiple Intersections for Cooperative Perception
Karthikeyan Chandra Sekaran, Markus Geisler, Dominik RöÃle +6
Recent cooperative perception datasets have played a crucial role in advancing smart mobility applications by enabling information exchange between intelligent agents, helping to o…
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…