7 citations · 14 across the 14 of their papers we have counts for
10 papers · 1 filter
GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization
Xiaosong Jia, Bowen Yang, Zuhao Ge +17
Vision-Language-Action (VLA) models aim for general robot learning by aligning action as a modality within powerful Vision-Language Models (VLMs). Existing VLAs rely on end-to-end…
: Resource-Aware Robust Manipulation via Taming Distributional Inconsistencies
Checheng Yu, Chonghao Sima, Gangcheng Jiang +14
High-reliability long-horizon robotic manipulation has traditionally relied on large-scale data and compute to understand complex real-world dynamics. However, we identify that the…
Seeing Farther and Smarter: Value-Guided Multi-Path Reflection for VLM Policy Optimization
Yanting Yang, Shenyuan Gao, Qingwen Bu +2
Solving complex, long-horizon robotic manipulation tasks requires a deep understanding of physical interactions, reasoning about their long-term consequences, and precise high-leve…
WholeBodyVLA: Towards Unified Latent VLA for Whole-Body Loco-Manipulation Control
Haoran Jiang, Jin Chen, Qingwen Bu +8
Humanoid robots require precise locomotion and dexterous manipulation to perform challenging loco-manipulation tasks. Yet existing approaches, modular or end-to-end, are deficient…
Agility Meets Stability: Versatile Humanoid Control with Heterogeneous Data
Yixuan Pan, Ruoyi Qiao, Li Chen +8
Humanoid robots are envisioned to perform a wide range of tasks in human-centered environments, requiring controllers that combine agility with robust balance. Recent advances in l…
UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
Qingwen Bu, Yanting Yang, Jisong Cai +5
A generalist robot should perform effectively across various environments. However, most existing approaches heavily rely on scaling action-annotated data to enhance their capabili…
AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems
AgiBot World Contributors, AgiBot-World-Contributors, Qingwen Bu +50
We explore how scalable robot data can address real-world challenges for generalized robotic manipulation. Introducing AgiBot World, a large-scale platform comprising over 1 millio…
Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulation
Qingwen Bu, Jia Zeng, Li Chen +7
Despite significant progress in robotics and embodied AI in recent years, deploying robots for long-horizon tasks remains a great challenge. Majority of prior arts adhere to an ope…
Towards Synergistic, Generalized, and Efficient Dual-System for Robotic Manipulation
Qingwen Bu, Hongyang Li, Li Chen +5
The increasing demand for versatile robotic systems to operate in diverse and dynamic environments has emphasized the importance of a generalist policy, which leverages a large cro…
Learning Manipulation by Predicting Interaction
Jia Zeng, Qingwen Bu, Bangjun Wang +12
Representation learning approaches for robotic manipulation have boomed in recent years. Due to the scarcity of in-domain robot data, prevailing methodologies tend to leverage larg…