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cs.RO2026

Barrier-Constrained Guidance For Real-time Asynchronous VLA Execution

Wenbo Yu, Jifan Li, Wenke Xia +5

While asynchronous execution enables VLA models to operate in real-time environments by predicting the next chunk during execution, it inevitably introduces boundary misalignment w…

cs.RO2026

GAINS: Leveraging Inconsistent Human Intervention Signals in Reinforcement Learning

Xinyi Zhang, Yinuo Zhao, Pei Ren +7

Correcting robot manipulation policies through human intervention holds great promise for real-world deployment, yet human operators are inherently imperfect in both the actions th…

cs.RO2026

Robo-ValueRL: Reliable Value Estimation for Offline-to-Online Reinforcement Learning

Wenke Xia, Pei Ren, Wenbo Yu +10

Offline-to-online reinforcement learning is promising for generalizable robotic manipulation, yet its full-stack complexity obscures reproduction and diagnosis. Within such systems…

cs.RO2026

VLAMotor: Test-Guided Enhancement of Vision-Language-Action Models via Agent-BasedData Synthesis

Zeqin Liao, Peifan Ren, Zixu Gao +6

Vision-Language-Action (VLA) models follow a data-driven paradigm and are constrained by the coverage of training data, making them prone to failure on edge-case configurations aft…

cs.RO2026

RoboGene: Diversity-Driven Agentic Task Generation Framework for VLA Pre-training

Yixue Zhang, Kun Wu, Zhi Gao +12

The pursuit of general-purpose robotic manipulation is hindered by the scarcity of diverse, real-world interaction data. Unlike large-scale web vision-language data, robotic data c…

cs.RO2025

Real-world Reinforcement Learning from Suboptimal Interventions

Yinuo Zhao, Huiqian Jin, Lechun Jiang +9

Real-world reinforcement learning (RL) offers a promising approach to training precise and dexterous robotic manipulation policies in an online manner, enabling robots to learn fro…

cs.RO2025

RoboMIND 2.0: A Multimodal, Bimanual Mobile Manipulation Dataset for Generalizable Embodied Intelligence

Chengkai Hou, Kun Wu, Jiaming Liu +30

While data-driven imitation learning has revolutionized robotic manipulation, current approaches remain constrained by the scarcity of large-scale, diverse real-world demonstration…

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

RoboPARA: Dual-Arm Robot Planning with Parallel Allocation and Recomposition Across Tasks

Shiying Duan, Pei Ren, Nanxiang Jiang +5

Dual-arm robots play a crucial role in improving efficiency and flexibility in complex multitasking scenarios. While existing methods have achieved promising results in task planni…