AI RESEARCH
Adversarial Attacks on Robot Localization Systems via Deep Feature Perturbation
arXiv CS.CV
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ArXi:2606.01892v1 Announce Type: new Robot localization systems are critical for autonomous navigation and safety. Adversarial perturbations can mislead these systems, resulting in mislocalization, navigation errors, or unsafe interactions, especially in mission-critical scenarios. This paper investigates the vulnerability of deep learning based localization pipelines to adversarial attacks. We propose a novel framework for generating adversarial queries that specifically tar Quantization (PQ) in visual localization systems.