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cs.RO2026

You Only Touch Once: 6-DoF Object Pose Estimation from Single Tactile Contact

Pengfei Ye, Yuxiang Ma, Haonan Chen +5

Accurate 6-DoF object pose estimation is fundamental to robotic manipulation, yet vision-based methods often fail under occlusion, poor lighting, and reflective or transparent surf…

cs.RO2026

RoboFlow4D: A Lightweight Flow World Model Toward Real-Time Flow-Guided Robotic Manipulation

Sixu Lin, Junliang Chen, Huaiyuan Xu +8

Planning and acting in 3D environments is a fundamental capability for robotic manipulation in the real world. Although prior work has explored predictive flow planners to guide 3D…

cs.RO2026

PhySPRING: Structure-Preserving Reduction of Physics-Informed Twins via GNN

Yixiong Jing, Xingyuan Chen, Guangming Wang +3

Physics-based digital twins aim to predict the dynamics of real-world objects under interaction, enabling real-to-sim-to-real applications in robotics. Current approaches reconstru…

cs.RO2026

Continually Evolving Skill Knowledge in Vision Language Action Model

Yuxuan Wu, Guangming Wang, Zhiheng Yang +4

Vision-language-action (VLA) models show promising knowledge accumulation ability from pretraining, yet continual learning in VLA remains challenging, especially for efficient adap…

cs.RO2026

ActionReasoning: Robot Action Reasoning in 3D Space with LLM for Robotic Brick Stacking

Guangming Wang, Qizhen Ying, Yixiong Jing +2

Classical robotic systems typically rely on custom planners designed for constrained environments. While effective in restricted settings, these systems lack generalization capabil…