8 papers
MaskVLA: Visual Masking Against Trajectory Overfitting of Vision-Language-Action Model
Yuxuan Jiang, Jiaying Huang, Ge Wang +9
Vision-Language-Action (VLA) models integrate vision-language understanding with executable robot actions, enabling end-to-end learning for robot control. However, our empirical an…
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…
SVLL: Staged Vision-Language Learning for Physically Grounded Embodied Task Planning
Yuyuan Yang, Junkun Hong, Hongrong Wang +11
Embodied task planning demands vision-language models to generate action sequences that are both visually grounded and causally coherent over time. However, existing training parad…
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…
STMA: A Spatio-Temporal Memory Agent for Long-Horizon Embodied Task Planning
Mingcong Lei, Yiming Zhao, Ge Wang +4
A key objective of embodied intelligence is enabling agents to perform long-horizon tasks in dynamic environments while maintaining robust decision-making and adaptability. To achi…
Multi-Fidelity Reinforcement Learning for Time-Optimal Quadrotor Re-planning
Gilhyun Ryou, Geoffrey Wang, Sertac Karaman
High-speed online trajectory planning for UAVs poses a significant challenge due to the need for precise modeling of complex dynamics while also being constrained by computational…