From the 1 of 11 linked papers with an AI index.
11 papers
AtlasVLA: Persistent World-Ego State Modeling for Vision-Language-Action Models
Guiyu Zhao, Longteng Guo, Yanghong Mei +7
While Vision-Language-Action (VLA) models have advanced embodied AI, their fundamentally reactive paradigm severely limits performance in partially observable and long-horizon task…
Robust-WAM: Bridging Generative Pretraining and Semantic Foresight in World-Action Models
Haodong Yan, Junfeng Li, Junjie He +12
Mainstream World-Action Models (WAMs) adapt pretrained video generation models (VGMs) for robot control, transferring their learned dynamics prior for action prediction. These VGMs…
GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch
GigaWorld Team, Angen Ye, Angyuan Ma +26
The paper introduces GigaWorld-Policy-0.5, a robot control model that learns from future visual dynamics during training but generates actions only at inference, achieving faster (…
SurveilNav: Collaborative Object Goal Navigation with Robot and Surveillance System
Ming-Ming Yu, Qunbo Wang, Rongtao Xu +5
With the growing deployment of surveillance systems in factories, offices, and homes, integrating them with robots offers a promising direction for collaborative and efficient task…
NavWM: A Unified Navigation World Model for Foresight-Driven Planning
Yanghong Mei, Longteng Guo, Ming-Ming Yu +3
Conventional visual navigation policies often struggle with myopic decision-making and mode collapse in complex environments. While world models offer a promising alternative, exis…
C-NAV: Towards Self-Evolving Continual Object Navigation in Open World
Ming-Ming Yu, Fei Zhu, Wenzhuo Liu +4
Embodied agents are expected to perform object navigation in dynamic, open-world environments. However, existing approaches typically rely on static trajectories and a fixed set of…