3 papers
cs.AI2026
CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving
Junyao Wang, Yulin Xu, Yu Li +2
Modern autonomous vehicles are equipped with multiple sensors, such as cameras, LiDAR, and radar, for comprehensive environmental perception. However, robust cross-modal feature fu…
cs.RO2026
HydraCollab: Adaptive Collaborative-Perception for Distributed Autonomous Systems
Luke Chen, Cheng-Ju Wu, David R. Martin +3
Collaborative-perception enables multi-robot systems to enhance situational awareness by sharing perceptual information. Existing collaborative-perception systems face an inherent…
cs.CV2025
Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception
Luke Chen, Junyao Wang, Trier Mortlock +2
Uncertainty Quantification (UQ) is crucial for ensuring the reliability of machine learning models deployed in real-world autonomous systems. However, existing approaches typically…