Recent Vision-Language-Action (VLA) models increasingly use natural-language instructions to condition autonomous driving behavior. Yet existing closed-loop benchmarks primarily measure route completion, safety, and rule compliance, leaving a fundamental question unresolved: does language actually determine which feasi...
Zi-Han You, Ze-Hua Fan, Wenqi Lyu et al.· 0 citations
Action-chunking policies predict multi-step control sequences, but a fundamental question remains: how much of a predicted action chunk should be committed before replanning? Existing systems typically execute a fixed-length prefix, implicitly assuming that the same execution horizon remains trustworthy across states....
Yu-Yan Li, Yu-Jian Wang, Yu-Song Huang et al.· 0 citations
Most vision-language-action (VLA) models rely on current observations and lose task-relevant evidence once it leaves view, limiting performance on long-horizon, memory-dependent tasks. Existing efforts incorporate compressed historical features or sparse visual keyframes. However, isolated snapshots can leave the polic...
Yu-Heng Na, Zhi-De Zhong, Jun-Jie He et al.· 0 citations
Robotic data generation is a promising paradigm for scaling robot learning without collecting large-scale real-world data. However, generating geometrically diverse yet physically valid data for contact-rich tasks remains challenging, especially when success depends on precise geometric interfaces. Standard shape augme...
Tian-Yi Xiang, Xupeng Xie, Jia-Hang Cao et al.· 0 citations
Vision-language-action models benefit from the understanding and reasoning capabilities of pretrained vision-language models, but action-only supervision provides limited grounding in world dynamics. Conversely, world-action models inherit spatiotemporal priors from video generation models, yet remain limited in semant...
Wen-Xuan Song, Jia-Yi Chen, Jing-Bo Wang et al.· 1 citation
World-Action Models (WAMs) couple visual dynamics with action prediction, bringing the rich priors of pretrained video models to robotic manipulation. However, their multi-view interfaces typically tile images or concatenate tokens, leaving the geometric relationships among synchronized cameras implicit. This makes it...
Wen-Bo Chen, Tian-Fu Li, Hao-Xuan Xu et al.· 0 citations
Vision-Language-Action models are increasingly effective for robotic manipulation, yet most predict actions directly from current observations without explicitly modeling future scene evolution. Recent methods introduce future prediction to improve action generation, but dense future modeling often requires expensive i...
Tian-Fu Li, Hao-Xuan Xu, Wen-Bo Chen et al.· 0 citations
This work designs a hybrid architecture that combines sparse anchors with an offset refinement module for efficient multi-modal trajectory prediction and adopts a two-stage training paradigm consisting of pretraining and reward-guided fine-tuning, demonstrating superior performance under real-time constraints.
Cheng-Lin Chen, Lu-Jia Wang, Xin-Hu Zheng et al.· 0 citations
This work proposes an object--path graph that unifies open-vocabulary semantic reasoning with topological navigation, and introduces a navigation strategy that combines global path planning with local inter-node execution through lightweight node localization and semantic visual servoing, enabling navigation directly o...
Lin-Wei Zheng, Dao-Jie Peng, Bing-Tao Wang et al.· 0 citations
Vision-Language-Action (VLA) models have become a powerful paradigm for robot manipulation, but training a single generalist policy for heterogeneous robot embodiments remains an open problem. Existing methods have two main limitations. First, they underuse dynamics priors shared across diverse visual and interaction d...
Jun-Feng Li, Junjie He, Zhi-De Zhong et al.· 1 citation
This work introduces ActiveScale, a framework that advances active perception through coordinated model, data, and hardware designs, and introduces Active-perception Mobile-manipulation Platform (AMP), a robotic platform that supports active perception and mobile manipulation through single-operator teleoperation, enab...
Shuai-Tao Zhou, Kai-Sheng Pang, Wen-Xuan Song et al.· 1 citation
SimFuse3D is introduced, which preserves the target placement and repairs the associated pseudo object using measured geometry from labeled source scans, and achieves the best performance among the compared adaptation methods on nearly all metrics.
Yong-Chun Lin, Xin-Liang Zhang, Yun Zou et al.· 0 citations
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