3 papers
cs.RO2026
TACO: TActile World Model as a Self-COrrector forScalable VLA Post-Training
Shengbang Liu, Yueru Jia, Yuyang Yan +7
Vision-Language-Action (VLA) models have shown promising generalization in robotic manipulation, but they still struggle with contact-rich tasks, where minor contact perturbations…
cs.RO2026
Video2Act: A Dual-System Video Diffusion Policy with Robotic Spatio-Motional Modeling
Yueru Jia, Jiaming Liu, Shengbang Liu +7
Robust perception and dynamics modeling are fundamental to real-world robotic policy learning. Recent methods employ video diffusion models (VDMs) to enhance robotic policies, impr…
cs.RO2025
Decoding RobKiNet: Insights into Efficient Training of Robotic Kinematics Informed Neural Network
Yanlong Peng, Zhigang Wang, Ziwen He +4
In robots task and motion planning (TAMP), it is crucial to sample within the robot's configuration space to meet task-level global constraints and enhance the efficiency of subseq…