adversarial training 1color robustness 1illumination attack 1robotic manipulation 1vision-language-action 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.RO2026
Lights, Camera, Malfunction: When Illumination Robustness Leaves VLA Models Blind to Color
Marino Watanabe, Takami Sato, Kentaro Yoshioka
The paper studies how Vision‑Language‑Action (VLA) robot models fail under targeted spotlight illumination, reveals that common data augmentations cause them to ignore color, and i…
cs.CV2026
Neural Reconstruction of LiDAR Point Clouds under Jamming Attacks via Full-Waveform Representation and Simultaneous Laser Sensing
Ryo Yoshida, Takami Sato, Wenlun Zhang +7
LiDAR sensors are critical for autonomous driving perception, yet remain vulnerable to spoofing attacks. Jamming attacks inject high-frequency laser pulses that completely blind Li…
cs.RO2025
SLAMSpoof: Practical LiDAR Spoofing Attacks on Localization Systems Guided by Scan Matching Vulnerability Analysis
Rokuto Nagata, Kenji Koide, Yuki Hayakawa +6
Accurate localization is essential for enabling modern full self-driving services. These services heavily rely on map-based traffic information to reduce uncertainties in recognizi…