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20242026
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cs.RO2026

FreqPolicy: Efficient Flow-based Visuomotor Policy via Frequency Consistency

Yifei Su, Ning Liu, Dong Chen +6

Generative modeling-based visuomotor policies have been widely adopted in robotic manipulation, attributed to their ability to model multimodal action distributions. However, the h…

cs.RO2025

HACTS: a Human-As-Copilot Teleoperation System for Robot Learning

Zhiyuan Xu, Yinuo Zhao, Kun Wu +5

Teleoperation is essential for autonomous robot learning, especially in manipulation tasks that require human demonstrations or corrections. However, most existing systems only off…

cs.RO2025

SwitchVLA: Execution-Aware Task Switching for Vision-Language-Action Models

Meng Li, Zhen Zhao, Zhengping Che +7

Robots deployed in dynamic environments must be able to not only follow diverse language instructions but flexibly adapt when user intent changes mid-execution. While recent Vision…

cs.RO2025

TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation

Junjie Wen, Yichen Zhu, Jinming Li +9

Vision-Language-Action (VLA) models have shown remarkable potential in visuomotor control and instruction comprehension through end-to-end learning processes. However, current VLA…

cs.RO2025

Discrete Policy: Learning Disentangled Action Space for Multi-Task Robotic Manipulation

Kun Wu, Yichen Zhu, Jinming Li +4

Learning visuomotor policy for multi-task robotic manipulation has been a long-standing challenge for the robotics community. The difficulty lies in the diversity of action space:…

cs.RO2025

Learning from Imperfect Demonstrations with Self-Supervision for Robotic Manipulation

Kun Wu, Ning Liu, Zhen Zhao +5

Improving data utilization, especially for imperfect data from task failures, is crucial for robotic manipulation due to the challenging, time-consuming, and expensive data collect…