From the 2 of 15 linked papers with an AI index.
15 papers
FA-RDP: A Frequency-Adaptive Reactive Diffusion Policy for Contact-Rich Manipulation
Lifeng Zhuo, Wendi Chen, Han Xue +4
The paper introduces FA-RDP, a diffusion‑based policy that adapts its inference frequency during contact‑rich manipulation, using a multi‑frequency visual‑force transformer and a m…
Never Too Late for Force: Accelerating VLA Post-Training with Reactive Force Injection
Yi Wang, Wendi Chen, Zimo Wen +8
The paper introduces LIFT, a post‑training method that adds reactive force feedback to pretrained vision‑language‑action policies, enabling them to handle contact‑rich manipulation…
ActiveGlasses: Learning Manipulation with Active Vision from Ego-centric Human Demonstration
Yanwen Zou, Chenyang Shi, Wenye Yu +5
Large-scale real-world robot data collection is a prerequisite for bringing robots into everyday deployment. However, existing pipelines often rely on specialized handheld devices…
RoboPocket: Improve Robot Policies Instantly with Your Phone
Junjie Fang, Wendi Chen, Han Xue +7
Scaling imitation learning is fundamentally constrained by the efficiency of data collection. While handheld interfaces have emerged as a scalable solution for in-the-wild data acq…
Rethinking Camera Choice: An Empirical Study on Fisheye Camera Properties in Robotic Manipulation
Han Xue, Nan Min, Xiaotong Liu +5
The adoption of fisheye cameras in robotic manipulation, driven by their exceptionally wide Field of View (FoV), is rapidly outpacing a systematic understanding of their downstream…
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…