2 citations · 2 across the 5 of their papers we have counts for
5 papers
GhostTac: Manipulating Tactile Sensors without Physical Contact
Kun Wang, Xuancun Lu, Ruochen Zhou +6
Tactile sensors are integral components of modern robotic systems, enabling robots to perceive and interact with the physical environment through tactile feedback. Despite their im…
Phantom Menace: Exploring and Enhancing the Robustness of VLA Models Against Physical Sensor Attacks
Xuancun Lu, Jiaxiang Chen, Shilin Xiao +7
Vision-Language-Action (VLA) models revolutionize robotic systems by enabling end-to-end perception-to-action pipelines that integrate multiple sensory modalities, such as visual s…
Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-Based Robots
Xuancun Lu, Zhengxian Huang, Xinfeng Li +4
LLM-based robots use Large Language Models (LLMs) as planners to translate natural language instructions into policies such as grasp(), move_to(), and open_gripper(). Jailbreak att…
PhantomLiDAR: Cross-modality Signal Injection Attacks against LiDAR
Zizhi Jin, Qinhong Jiang, Xuancun Lu +3
LiDAR (Light Detection and Ranging) is a pivotal sensor for autonomous driving, offering precise 3D spatial information. Previous signal attacks against LiDAR systems mainly exploi…
Inaudible Adversarial Perturbation: Manipulating the Recognition of User Speech in Real Time
Xinfeng Li, Chen Yan, Xuancun Lu +3
Automatic speech recognition (ASR) systems have been shown to be vulnerable to adversarial examples (AEs). Recent success all assumes that users will not notice or disrupt the atta…