10 papers · 1 filter
Rethink Before You Execute: Adaptive Execution for World Action Models
Feng Ye, Yiming Zhao, Yong Yu +5
World Action Models (WAMs) jointly predict future actions and the evolution of the environment. At each inference, a WAM generates a chunk of actions and the robot executes a fixed…
Interleaved POMDP Planning for Multi-Object Search in Unknown Multi-Room Household Environments
Ruochu Yang, Ziyi Xia, Huibo Zhang +6
Multi-object search in unknown household environments requires planning under extensive uncertainty - from unknown object locations to cluttered spaces with unobserved obstacles. P…
TSD: A Physics-Inspired Trajectory Saliency Detector for Efficient Imitation Learning
Yiming Zhao, Gongrui Ma, Qingkai Li +1
For imitation learning in robotic manipulation, high data collection costs result in the scarcity of high quality data. In this paper, we leverage the inherent heterogeneity of tra…
ReFPO: Reflow Regularization for Flow Matching Policy Gradients
Ge Wang, Yibo Peng, Fan Feng +10
We present Reflow-regularized Flow Matching Policy Gradients (ReFPO), a simple online RL method that adds explicit Reflow regularization to FPO for efficient flow-based control. We…
MimicIK: Real-Time Generative Inverse Kinematics from Teleoperation with FK Consistency
Jiahao Yang, Shenhao Yan, Fan Feng +5
Inverse kinematics (IK) remains a critical bottleneck for real-time robot manipulation. Classical numerical solvers achieve high geometric precision but often suffer from discontin…
Acting While Understanding: Asynchronous Semantic-Action Decoupling for Real-Time Vision-Language-Action Models
Shenhao Yan, Ge Wang, Qi Liu +7
Vision-Language-Action models (VLAs) have demonstrated strong task understanding and generalization in robotic manipulation, yet the high computational cost of full-model inference…
KoopmanFlow: Spectrally Decoupled Generative Control Policy via Koopman Structural Bias
Chengsi Yao, Ge Wang, Kai Kang +9
Generative Control Policies (GCPs) show immense promise in robotic manipulation but struggle to simultaneously model stable global motions and high-frequency local corrections. Whi…
RoboSeek: You Need to Interact with Your Objects
Yibo Peng, Jiahao Yang, Shenhao Yan +5
Optimizing and refining action execution through exploration and interaction is a promising way for robotic manipulation. However, practical approaches to interaction-driven roboti…
RoboMemory: A Brain-inspired Multi-memory Agentic Framework for Interactive Environmental Learning in Physical Embodied Systems
Mingcong Lei, Honghao Cai, Yuyuan Yang +16
Embodied intelligence aims to enable robots to learn, reason, and generalize robustly across complex real-world environments. However, existing approaches often struggle with parti…
CLEA: Closed-Loop Embodied Agent for Enhancing Task Execution in Dynamic Environments
Mingcong Lei, Ge Wang, Yiming Zhao +7
Large Language Models (LLMs) exhibit remarkable capabilities in the hierarchical decomposition of complex tasks through semantic reasoning. However, their application in embodied s…