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cs.RO2026

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…

cs.RO2026

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 (…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

EgoActor: Grounding Task Planning into Spatial-aware Egocentric Actions for Humanoid Robots via Visual-Language Models

Yu Bai, MingMing Yu, Chaojie Li +3

Deploying humanoid robots in real-world settings is fundamentally challenging, as it demands tight integration of perception, locomotion, and manipulation under partial-information…