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20242026
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cs.RO2026

Think at 5 Hz, Act at 20 Hz: Asynchronous Fast-Slow Vision-Language-Action Inference for Closed-Loop Driving

Yun Li, Jiachen Gong, Simon Thompson +7

Large language models bring instruction following and scene reasoning to end-to-end driving, but their inference latency collides with the control rate a vehicle requires. Existing…

cs.RO2026

Causal Scene Narration with Runtime Safety Supervision for Vision-Language-Action Driving

Yun Li, Yidu Zhang, Simon Thompson +2

Vision-Language-Action (VLA) models for autonomous driving must integrate diverse textual inputs, including navigation commands, hazard warnings, and traffic state descriptions, ye…

cs.RO2026

An Open-Source Modular Benchmark for Diffusion-Based Motion Planning in Closed-Loop Autonomous Driving

Yun Li, Simon Thompson, Yidu Zhang +2

Diffusion-based motion planners have achieved state-of-the-art results on benchmarks such as nuPlan, yet their evaluation within closed-loop production autonomous driving stacks re…

cs.RO2025

Towards Robust LiDAR Localization: Deep Learning-based Uncertainty Estimation

Minoo Dolatabadi, Fardin Ayar, Ehsan Javanmardi +2

LiDAR-based localization and SLAM often rely on iterative matching algorithms, particularly the Iterative Closest Point (ICP) algorithm, to align sensor data with pre-existing maps…

cs.RO2025

Towards Efficient Roadside LiDAR Deployment: A Fast Surrogate Metric Based on Entropy-Guided Visibility

Yuze Jiang, Ehsan Javanmardi, Manabu Tsukada +1

The deployment of roadside LiDAR sensors plays a crucial role in the development of Cooperative Intelligent Transport Systems (C-ITS). However, the high cost of LiDAR sensors neces…

cs.RO2025

Neural Error Covariance Estimation for Precise LiDAR Localization

Minoo Dolatabadi, Fardin Ayar, Ehsan Javanmardi +2

Autonomous vehicles have gained significant attention due to technological advancements and their potential to transform transportation. A critical challenge in this domain is prec…