collaborators

10 papers

cs.RO2026

FreeSpeed: Training-Free Speed Control for Generative Robot Policies

Yuxuan Hu, Shilin Shan, Qiheng Wang +4

Online control of execution speed is essential for deploying robot policies in real-world scenarios, as robots may need to speed up under time constraints or slow down to facilitat…

cs.RO2026

EMERGE-Policy: A Robot Mind Emerges Beyond a Single Policy

Zhirui Fang, Qingchi Yu, Ziyang Chen +18

A robot's effective ``mind'' need not reside in a single policy. It can emerge when specialized components perceive, reason, predict, act, verify, and remember within a shared orch…

cs.RO2026

FuncBridge: Towards Functional Tool-Use Generalization via Keypoint Trajectory Reasoning

Chuhao Zhou, Liquan Wang, Shuxin Cao +5

While humans readily repurpose a book, a stone, or a shoe to drive a nail, robots trained on specific tools fail to transfer the same function to novel ones -- a gap we formalize a…

cs.RO2026

ResCue: Residual Spatial Cueing for Language-Conditioned Imitation Learning

Yanzhe Tang, Xinyu Shao, Yuxuan Hu +8

Visual imitation policies must learn which image regions matter for action, whether applying the same operation to different objects or selecting a language-specified target. We in…

cs.RO2026

Rethinking Implicit Spatial Representation in Visuomotor Policy Learning

Xiangyu Chen, Yuxuan Hu, Chuhao Zhou +1

Generative model-based imitation learning has become a widely adopted paradigm for robotic manipulation, where policy performance depends critically on the conditioned visual repre…

cs.RO2026

MARS Policy: Multimodality Only When It Matters

Jindou Jia, Tuo An, Yuxuan Hu +7

Imitation learning has become a cornerstone for solving complex robotic manipulation tasks. In particular, multimodality, which enables robots to capture diverse yet valid behavior…

cs.RO2026

FLASH: Efficient Visuomotor Policy via Sparse Sampling

Jiaqi Bai, Jindou Jia, Yuxuan Hu +5

Generative models such as diffusion and flow matching have become dominant paradigms for visuomotor policy learning, yet their reliance on iterative denoising incurs high inference…

cs.RO2026

Trace-Focused Diffusion Policy for Multi-Modal Action Disambiguation in Long-Horizon Robotic Manipulation

Yuxuan Hu, Xiangyu Chen, Chuhao Zhou +4

Generative model-based policies have shown strong performance in imitation-based robotic manipulation by learning action distributions from demonstrations. However, in long-horizon…

cs.RO2026

Action-to-Action Flow Matching

Jindou Jia, Gen Li, Xiangyu Chen +5

Diffusion-based policies have recently achieved remarkable success in robotics by formulating action prediction as a conditional denoising process. However, the standard practice o…

cs.RO2025

DIPOLE: Fusing Vision and Geometry for Robust Visuomotor Generalization

Yikai Tang, Haoran Geng, Jindou Jia +5

Imitation learning has emerged as a crucial approach for acquiring visuomotor skills from demonstrations, where designing effective observation encoders is essential for policy gen…