collaborators

7 papers

cs.RO2026

: Toward Versatile Embodied Agents

Shengli Zhou, Xiangchen Wang, Jinrui Zhang +5

Embodied agents have demonstrated promising capabilities in interacting with physical environments. Yet, versatile embodied agents face three core bottlenecks: dynamic environmenta…

cs.RO2026

VGP-Nav: Metric-Aware Visual Geometric Perception for Robot Navigation

Hewei Pan, Weiye Zhu, Zekai Zhang +4

Reliable robotic navigation necessitates the seamless integration of accurate global localization and dense, metric-consistent obstacle perception. A common strategy to achieve the…

cs.RO2026

AnySlot: Goal-Conditioned Vision-Language-Action Policies for Zero-Shot Slot-Level Placement

Zhaofeng Hu, Sifan Zhou, Qinbo Zhang +4

Vision-Language-Action (VLA) policies have emerged as a versatile paradigm for generalist robotic manipulation. However, precise object placement under compositional language remai…

cs.RO2026

DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo

Hanwen Wang, Weizhi Zhao, Xiangyu Wang +11

Achieving human-level manipulation requires dexterous robotic hands capable of complex object interactions. Advancing such capabilities further demands standardized benchmarks for…

cs.RO2026

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model

Kaidong Zhang, Jian Zhang, Rongtao Xu +20

Vision-Language-Action (VLA) models have emerged as a powerful paradigm for open-world robot manipulation, but their practical deployment is often constrained by cost: billion-scal…

cs.CV2026

\textsc{NaVIDA}: Vision-Language Navigation with Inverse Dynamics Augmentation

Weiye Zhu, Zekai Zhang, Xiangchen Wang +5

Vision-and-Language Navigation (VLN) requires agents to interpret natural language instructions and act coherently in visually rich environments. However, most existing methods rel…