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Robo-Dopamine: General Process Reward Modeling for High-Precision Robotic Manipulation
Huajie Tan, Sixiang Chen, Yijie Xu +12
The primary obstacle for applying reinforcement learning (RL) to real-world robotics is the design of effective reward functions. While recently learning-based Process Reward Model…
Towards Cross-View Point Correspondence in Vision-Language Models
Yipu Wang, Yuheng Ji, Yuyang Liu +10
Cross-view correspondence is a fundamental capability for spatial understanding and embodied AI. However, it is still far from being realized in Vision-Language Models (VLMs), espe…
RoboMirror: Understand Before You Imitate for Video to Humanoid Locomotion
Zhe Li, Boan Zhu, Yangyang Wei +11
Humans learn locomotion through visual observation, interpreting visual content first before imitating actions. However, state-of-the-art humanoid locomotion systems rely on either…
Embodied Robot Manipulation in the Era of Foundation Models: Planning and Learning Perspectives
Shuanghao Bai, Wenxuan Song, Jiayi Chen +14
Recent advances in vision, language, and multimodal learning have significantly accelerated progress in robotic foundation models, with robotic manipulation remaining one of the mo…
Towards Spatial Trace with Reasoning in Vision-Language Models for Robotics
Enshen Zhou, Yibo Li, Jingkun An +12
Spatial tracing, as a fundamental embodied interaction ability for robots, is inherently challenging as it requires multi-step metric-grounded reasoning compounded with complex spa…
RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation
Shihan Wu, Xuecheng Liu, Shaoxuan Xie +81
Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due to the significant hardware hete…
PIGEON: VLM-Driven Object Navigation via Points of Interest Selection
Cheng Peng, Zhenzhe Zhang, Xiaobao Wei +7
Object navigation in unseen indoor environments requires agents to perform semantic search under partial observability. Vision-language models (VLMs) provide strong semantic-spatia…
RoboOS-NeXT: A Unified Memory-based Framework for Lifelong, Scalable, and Robust Multi-Robot Collaboration
Huajie Tan, Cheng Chi, Xiansheng Chen +21
The proliferation of collaborative robots across diverse tasks and embodiments presents a central challenge: achieving lifelong adaptability, scalable coordination, and robust sche…
From Language to Locomotion: Retargeting-free Humanoid Control via Motion Latent Guidance
Zhe Li, Cheng Chi, Yangyang Wei +7
Natural language offers a natural interface for humanoid robots, but existing language-guided humanoid locomotion pipelines remain cumbersome and untrustworthy. They typically deco…
Robobench: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models as Embodied Brain
Yulin Luo, Chun-Kai Fan, Menghang Dong +19
Building robots that can perceive, reason, and act in dynamic, unstructured environments remains a central challenge. Recent embodied systems often follow a dual-system paradigm, w…
TIGeR: Tool-Integrated Geometric Reasoning in Vision-Language Models for Robotics
Yi Han, Enshen Zhou, Shanyu Rong +6
Vision-Language Models (VLMs) have shown remarkable capabilities in spatial reasoning, yet they remain fundamentally limited to qualitative precision and lack the computational pre…
MathSticks: A Benchmark for Visual Symbolic Compositional Reasoning with Matchstick Puzzles
Yuheng Ji, Huajie Tan, Cheng Chi +8
We introduce \textsc{MathSticks}, a benchmark for Visual Symbolic Compositional Reasoning (VSCR), which unifies visual perception, symbolic manipulation, and arithmetic consistency…
RoboBrain 2.0 Technical Report
BAAI RoboBrain Team, Mingyu Cao, Huajie Tan +50
We introduce RoboBrain 2.0, our latest generation of embodied vision-language foundation models, designed to unify perception, reasoning, and planning for complex embodied tasks in…
RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics
Enshen Zhou, Jingkun An, Cheng Chi +8
Spatial referring is a fundamental capability of embodied robots to interact with the 3D physical world. However, even with the powerful pretrained vision language models (VLMs), r…