collaborators

5 papers

cs.RO2025

ImplicitRDP: An End-to-End Visual-Force Diffusion Policy with Structural Slow-Fast Learning

Wendi Chen, Han Xue, Yi Wang +6

Human-level contact-rich manipulation relies on the distinct roles of two key modalities: vision provides spatially rich but temporally slow global context, while force sensing cap…

cs.RO2025

ARMADA: Autonomous Online Failure Detection and Human Shared Control Empower Scalable Real-world Deployment and Adaptation

Wenye Yu, Jun Lv, Zixi Ying +3

Imitation learning has shown promise in learning from large-scale real-world datasets. However, pretrained policies usually perform poorly without sufficient in-domain data. Beside…

cs.RO2025

SOE: Sample-Efficient Robot Policy Self-Improvement via On-Manifold Exploration

Yang Jin, Jun Lv, Han Xue +3

Intelligent agents progress by continually refining their capabilities through actively exploring environments. Yet robot policies often lack sufficient exploration capability due…

cs.RO2025

Knowledge-Driven Imitation Learning: Enabling Generalization Across Diverse Conditions

Zhuochen Miao, Jun Lv, Hongjie Fang +2

Imitation learning has emerged as a powerful paradigm in robot manipulation, yet its generalization capability remains constrained by object-specific dependencies in limited expert…

cs.RO2025

SIME: Enhancing Policy Self-Improvement with Modal-level Exploration

Yang Jin, Jun Lv, Wenye Yu +3

Self-improvement requires robotic systems to initially learn from human-provided data and then gradually enhance their capabilities through interaction with the environment. This i…