arXiv:2606. 12109v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated remarkable zero-shot generalization in robotic manipulation, yet the vast majority of pre-trained pipelines remain strictly confined to low-DoF parallel grippers.
By Chuanke Pang, Junyi Huang, Zhijun Zhao, Yaobing Wang, Kun Xu, Xilun Ding
AdaRoboVLG is a Vision‑Language‑Grasp framework that separates a generalizable base grasp policy from task‑specific understanding. The base policy generates and evaluates physically feasible grasp candidates using kinematic mapping and force‑closure stability, while foundation‑model modules supply composable spatial, cognitive, and temporal priors that adapt grasp synthesis to different robotic hands and environments without retraining. Experiments show strong cross‑hand generalization, effective handling of diverse grasping challenges, and functional grasping in cluttered, dynamic settings.
By Sixu Yan, Shikang Wang, Binhua Huang, Xuanlai Tang, Guohua Fan, Fan Huang, Haoxuan Li, Yongkang Li, Yuhan Li, Bencheng Liao, Zeyu Zhang, Wenyu Liu, Hangxin Liu, Xinggang Wang
arXiv:2606. 10614v1 Announce Type: cross Abstract: Robotic foundation models pre-trained on human demonstration videos have shown promise, but a significant embodiment gap remains when the resulting policies are deployed on real robots.
By Beomjun Kim, Seong Hyeon Park, Seunghoon Sim, Seungjun Moon, Sanghyeok Lee, Jinwoo Shin
arXiv:2609.34182v2 Announce Type: replace-cross
Abstract: Dexterous manipulation requires tactile feedback. However, robot tactile demonstrations are difficult to scale,because dexterous-hand teleope...
By Wenqiao Li, Qianyou Zhao, Jiawen Hao, Xuezhou Zhu, Tengyu Liu, Kaifeng Zhang, Chuan Wen, Siyuan Huang
arXiv:2608.22449v1 Announce Type: cross
Abstract: Forecasting dexterous hand motions from egocentric observations is fundamental to intelligent interactive systems. Existing VLM-based methods typical...
By Wen Wang, Ruibing Hou, Hong Chang, Shiguang Shan, Xilin Chen
arXiv:2607. 04591v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated strong capabilities in robotic manipulation by integrating visual perception, language understanding, and robot action generation.
By Xinchuan Qiu, Yi Yu