MirrorDrift: Actuated Mirror-Based Attacks on LiDAR SLAM
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arXiv
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| Format: | Preprint |
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2026
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| author | Nagata, Rokuto Koide, Kenji Ikeda, Kazuma Sako, Ozora Horie, Shion Yoshioka, Kentaro |
| author_facet | Nagata, Rokuto Koide, Kenji Ikeda, Kazuma Sako, Ozora Horie, Shion Yoshioka, Kentaro |
| contents | LiDAR SLAM provides high-accuracy localization but is fragile to point-cloud corruption because scan matching assumes geometric consistency. Prior physical attacks on LiDAR SLAM largely rely on LiDAR spoofing via external signal injection, which requires sensor-specific timing knowledge and is increasingly mitigated by modern defense mechanisms such as timing obfuscation and injection rejection. In this work, we show that specular reflection offers an injection-free alternative and demonstrate an attack, MirrorDrift, that uses an actuated planar mirror to cause ghost points in LiDAR scans and systematically bias scan-matching correspondences. MirrorDrift optimizes mirror placement, alignment, and actuation. In simulation, it increases the average pose error (APE) by 6.1x over random placement, degrading three SLAM systems to 2.29-3.31 m mean APE. In real-world experiments on a modern LiDAR with state-of-the-art interference mitigation, it induces localization errors of up to 6.03 m. To the best of our knowledge, this is the first successful SLAM-targeted attack against production-grade secure LiDARs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_11364 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | MirrorDrift: Actuated Mirror-Based Attacks on LiDAR SLAM Nagata, Rokuto Koide, Kenji Ikeda, Kazuma Sako, Ozora Horie, Shion Yoshioka, Kentaro Robotics LiDAR SLAM provides high-accuracy localization but is fragile to point-cloud corruption because scan matching assumes geometric consistency. Prior physical attacks on LiDAR SLAM largely rely on LiDAR spoofing via external signal injection, which requires sensor-specific timing knowledge and is increasingly mitigated by modern defense mechanisms such as timing obfuscation and injection rejection. In this work, we show that specular reflection offers an injection-free alternative and demonstrate an attack, MirrorDrift, that uses an actuated planar mirror to cause ghost points in LiDAR scans and systematically bias scan-matching correspondences. MirrorDrift optimizes mirror placement, alignment, and actuation. In simulation, it increases the average pose error (APE) by 6.1x over random placement, degrading three SLAM systems to 2.29-3.31 m mean APE. In real-world experiments on a modern LiDAR with state-of-the-art interference mitigation, it induces localization errors of up to 6.03 m. To the best of our knowledge, this is the first successful SLAM-targeted attack against production-grade secure LiDARs. |
| title | MirrorDrift: Actuated Mirror-Based Attacks on LiDAR SLAM |
| topic | Robotics |
| url | https://arxiv.org/abs/2603.11364 |