Tactile sensing provides essential contact information for robotic manipulation, yet incorporating it into pretrained vision-language-action (VLA) models remains challenging. A common concern is that simply introducing touch during task-specific fine-tuning may fail to bridge the cross-modal gap, yielding limited gains...
Chen Yang, Lin-Zhe Shi, Chang Jie Wu et al.· 0 citations
Humanoid whole-body manipulation has advanced rapidly, enabling policies to coordinate locomotion, posture, bimanual interaction, and dexterous hand movements. Meanwhile, egocentric human videos provide diverse examples of everyday interactions across objects and scenes, offering scalable supervision without robot oper...
Chong-Yang Xu, Zhao Wu, Jin Chen et al.· 0 citations
EgoHumanoid-V2 is presented, the first egocentric human-to-humanoid skill transfer framework for coordinated whole-body loco-manipulation, which improves end-effector pose accuracy while preserving whole-body coordination and uses robot-arm rendering and training-time image augmentation to reduce the visual embodiment...
Jin Chen, Yi-Ming Jiang, Chong-Yang Xu et al.· 0 citations
DLAM, a distributional latent-action model that represents each transition as a diagonal Gaussian, is introduced, a distributional latent-action model that learns more temporally consistent latent dynamics than existing latent-action baselines and achieves stronger direct and cumulative reconstruction on held-out video...
Zuojin Tang, Feifan Luo, Haoyun Liu et al.· arXiv.org· 0 citations
Semantic-Temporal WAM (ST-WAM) is proposed to improve action robustness by using DINOv3 as a shared semantic representation for future prediction and history retrieval while retaining fine-grained VAE dynamics, demonstrating that semantic-temporal modeling effectively complements pixel-generative dynamics for robust ma...
Mingxin Wang, Bin Hu, Bin Qian et al.· arXiv.org· 5 citations· ⚡1
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