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arXiv · 2603.27273

Robust Global-Local Behavior Arbitration via Continuous Command Fusion Under LiDAR Errors

Mohamed Elgouhary·Amr S. El-Wakeel
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Abstract

Modular autonomous driving systems must coordinate global progress objectives with local safety-driven reactions under imperfect sensing and strict real-time constraints. This paper presents a ROS2-native arbitration module that continuously fuses the outputs of two unchanged and interpretable controllers: a global reference-tracking controller based on Pure Pursuit and a reactive LiDAR-based Gap Follow controller. At each control step, both controllers propose Ackermann commands, and a PPO-trained policy predicts a continuous gate from a compact feature observation to produce a single fused drive command, augmented with practical safety checks. For comparison under identical ROS topic inputs and control rate, we implement a lightweight sampling-based predictive baseline. Robustness is evaluated using a ROS2 impairment protocol that injects LiDAR noise, delay, and dropout, and additionally sweeps forward-cone false short-range outliers. In a repeatable close-proximity passing scenario, we report safe success and failure rates together with per-step end-to-end controller runtime as sensing stress increases. The study is intended as a command-level robustness evaluation in a modular ROS2 setting, not as a replacement for planning-level interaction reasoning.

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Mohamed Elgouhary, Amr S. El-Wakeel. 2026-03-28. Robust Global-Local Behavior Arbitration via Continuous Command Fusion Under LiDAR Errors. https://arxiv.org/abs/2603.27273

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