15 papers
TrapVLA: Trapping Vision-Language-Action Models in Configured Failure Modes
Jun-Hui Liu, Kun-Yu Lin, Yi-Lin Wei +9
This work introduces Configured Failure Trapping, a novel backdoor attack task against Vision-Language-Action (VLA) models, which aims to activate attacks through stealthy textual…
RoboSynChallenge: Mastering Real-World Dexterity via Generalizing Synthesized Manipulation Skills
Runyi Zhao, Ruixin Wu, Chengkun Li +15
Achieving generalizable robotic manipulation remains a central challenge in embodied intelligence. Despite rapid advances in model architectures and learning algorithms, progress i…
DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration
Haoran Liao, Pengyue Wang, Shuoyu Chen +10
Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that are moving or require rapid adj…
A Closed-Loop Multi-Agent Framework for Robust Multi-Robot Manipulation
Yi-Xiang He, Lan Wei, Haoming Cen +6
Multi-robot systems provide the parallelism and redundancy necessary for long-horizon tasks, while Large Language Models (LLMs) offer the reasoning capabilities to decompose these…
HATS: A Human-Agent Teleoperation System for Multi-Arm Data Collection
Zesen Lin, Jian-Jian Jiang, Haoming Cen +3
Many real-world manipulation scenarios, such as handling complex collaborative tasks and dealing with large workspaces, require coordination of more than two robotic arms. Conseque…
DexGrasp-Zero: A Morphology-Aligned Policy for Zero-Shot Cross-Embodiment Dexterous Grasping
Yuliang Wu, Yanhan Lin, WengKit Lao +4
To meet the demands of increasingly diverse dexterous hand hardware, it is crucial to develop a policy that enables zero-shot cross-embodiment grasping without redundant re-learnin…