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From the 1 of 17 linked papers with an AI index.

collaborators

17 papers

cs.RO2026

CheckVLA: Execution-Time Verification with Action-Conditioned World Model for Long-Horizon Mobile Manipulation

Yushan Liu, Peibo Sun, Xintao Chao +8

The paper introduces CheckVLA, a system that uses a frozen action‑conditioned world model to verify and intervene during long‑horizon mobile manipulation when execution deviates fr…

cs.RO2026

FutureNav: Unified World-Action Modeling for Vision-and-Language Navigation

Lingfeng Zhang, Zeying Gong, Xiaoshuai Hao +7

Vision-and-language navigation (VLN) in continuous environments requires an agent to ground instructions in egocentric observations while maintaining spatial understanding across l…

cs.RO2026

OneVLA: A Unified Framework for Embodied Tasks

Lingfeng Zhang, Xiaoshuai Hao, Yingbo Tang +10

Navigation and manipulation are fundamental capabilities of embodied intelligence, enabling robots to interpret natural language commands and interact physically with their surroun…

cs.RO2026

Learning Human-Intention Priors from Large-Scale Human Demonstrations for Robotic Manipulation

Yifan Xie, YuAn Wang, Guangyu Chen +3

Human videos contain rich manipulation priors, but using them for robot learning remains difficult because raw observations entangle scene understanding, human motion, and embodime…

cs.RO2026

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations

Zhengru Fang, Yu Guo, Fei Liu +5

Real-world visual systems face time-varying perturbations, including weather, sensor noise, compression artifacts, and background distractions. Existing image restoration methods a…

cs.RO2026

OA-WAM: Object-Addressable World Action Model for Robust Robot Manipulation

Yushan Liu, Peibo Sun, Shoujie Li +7

World Action Models (WAMs) enhance Vision-Language-Action policies by jointly predicting scene evolution and robot actions, but existing methods usually represent the predicted wor…