Detection of Adversarial Attacks in Robotic Perception

Ziad Sharawy, Mohammad Nakshbandi, Sorin Mihai Grigorescu
3/30/2026
cs.CVcs.AIcs.CR

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Abstract

Deep Neural Networks (DNNs) achieve strong performance in semantic segmentation for robotic perception but remain vulnerable to adversarial attacks, threatening safety-critical applications. While robustness has been studied for image classification, semantic segmentation in robotic contexts requires specialized architectures and detection strategies.

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Cite this paper

@article{sharawy2026detection,
  title  = {Detection of Adversarial Attacks in Robotic Perception},
  author = {Ziad Sharawy and Mohammad Nakshbandi and Sorin Mihai Grigorescu},
  year   = {2026},
  eprint = {2603.28594},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2603.28594v2}
}

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