9 papers · 1 filter
AtomEgo: Exploring Ego-Robot Integration for Embodied Foundation Model Pretraining
Di Wu, Dongchen Zheng, Junhe Sheng +8
Embodied foundation models are constrained by the limited scale and diversity of robot demonstrations, motivating the use of large-scale egocentric human interaction data. However,…
FAN: Foresight Action Normalization for Continual Adaptation of Vision-Language-Action Models
Yijun Hong, Jiarun Zhu, Xiaoquan Sun +6
Vision-Language-Action (VLA) models pre-trained on large-scale, closed datasets have demonstrated remarkable success across diverse robotic manipulation tasks. However, their long-…
Unified Condition-Action Modeling for Accurate One-Step Action Generation
Xinyu Zhou, Zikun Cai, Kuangji Zuo +7
Robot manipulation requires policies that are both accurate and efficient, as robot control must respond to changing observations under tight latency constraints. Recent diffusion…
SAM3D-Guided Object-Centric Representation Alignment for Vision-Language-Action Models
Zonghe Liu, Shanyuan Jie, Xiaoquan Sun +4
Vision-Language-Action (VLA) models have shown strong potential for general robot manipulation, but most existing models rely on 2D visual-language backbones and lack fine-grained…
CWI: Composite Humanoid Whole-Body Imitation System for Loco-manipulation
Wenqi Ge, Junde Guo, Zhen Fu +3
Achieving everyday tasks with humanoid robots requires coordinating stable locomotion with versatile manipulation. However, existing whole-body controllers still face significant c…
HiMem-WAM: Hierarchical Memory-Gated World Action Models for Robotic Manipulation
Xiaoquan Sun, Ruijian Zhang, Chen Cao +12
World Action Models (WAMs) have emerged as a new powerful paradigm for embodied intelligence, learning action-relevant visual dynamics that significantly enhance generalization and…
Can Vision-Language-Action Models Learn from Real-World Data Continually without Forgetting?
Jiarun Zhu, Yijun Hong, Xiaoquan Sun +7
Vision-Language-Action (VLA) models provide a promising foundation for general-purpose robotics, yet their real-world deployment demands the ability to continually acquire new skil…
AIM: Intent-Aware Unified world action Modeling with Spatial Value Maps
Liaoyuan Fan, Zetian Xu, Chen Cao +3
Pretrained video generation models provide strong priors for robot control, but existing unified world action models still struggle to decode reliable actions without substantial r…
A Survey of Behavior Foundation Model: Next-Generation Whole-Body Control System of Humanoid Robots
Mingqi Yuan, Tao Yu, Wenqi Ge +8
Humanoid robots are drawing significant attention as versatile platforms for complex motor control, human-robot interaction, and general-purpose physical intelligence. However, ach…