8 papers · 1 filter
VEGA: Learning Navigation VLAs from In-the-Wild Egocentric Video with Geometric Trajectory Supervision
Gershom Seneviratne, Yohan Abeysinghe, Jianyu An +3
We introduce VEGA, an approach for training navigation VisionLanguage-Action (VLA) models from unlabeled egocentric navigation videos. Internet-scale egocentric videos provide a sc…
Act on What You See: Unlocking Safe Social Navigation in Vision-Language-Action Models
Qingzi Wang, Xiyang Wu, Guangyao Shi +3
Safe social navigation requires robots to distinguish people from ordinary obstacles and to react before danger becomes imminent. We show that pretrained Vision-Language-Action (VL…
SABER: A Stealthy Agentic Black-Box Attack Framework for Vision-Language-Action Models
Xiyang Wu, Guangyao Shi, Qingzi Wang +3
Vision-language-action (VLA) models enable robots to follow natural-language instructions grounded in visual observations, but the instruction channel also introduces a critical vu…
MorFiC: Fixing Value Miscalibration for Zero-Shot Quadruped Transfer
Prakhar Mishra, Amir Hossain Raj, Xuesu Xiao +1
Generalizing learned locomotion policies across quadrupedal robots with different morphologies remains a challenge. Policies trained on a single robot often fail when deployed on e…
TransCurriculum: Multi-Dimensional Curriculum Learning for Fast & Stable Locomotion
Prakhar Mishra, Amir Hossain Raj, Xuesu Xiao +1
High-speed legged locomotion struggles with stability and transfer losses at higher command velocities during deployment. One reason is that most curricula vary difficulty along si…
CHOP: Counterfactual Human Preference Labels Improve Obstacle Avoidance in Visuomotor Navigation Policies
Gershom Seneviratne, Jianyu An, Vaibhav Shende +6
Visuomotor navigation policies have shown strong perception-action coupling for embodied agents, yet they often struggle with safe navigation and dynamic obstacle avoidance in comp…