Robotics & Embodied AI

RoboBrain 2.5: Depth in Sight, Time in Mind

HHuajie TanEEnshen ZhouZZhiyu LiYYijie XuYYuheng JiXXiansheng ChenCCheng ChiPPengwei WangHHuizhu JiaYYulong AoMMingyu CaoSSixiang ChenZZhe LiMMengzhen LiuZZixiao WangSShanyu RongYYaoxu LyuZZhongxia ZhaoPPeterson CoYYibo LiYYi HanSShaoxuan XieGGuocai YaoSSongjing WangLLeiduo ZhangXXi YangYYance JiaoDDonghai ShiKKunchang XieSShaokai NieCChunlei MenYYonghua LinZZhongyuan WangTTiejun HuangSShanghang Zhang
arXiv ID
2601.14352
Published
January 20, 2026
Authors
35
Hugging Face Likes
8
Comments
1

Abstract

We introduce RoboBrain 2.5, a next-generation embodied AI foundation model that advances general perception, spatial reasoning, and temporal modeling through extensive training on high-quality spatiotemporal supervision. Building upon its predecessor, RoboBrain 2.5 introduces two major capability upgrades. Specifically, it unlocks Precise 3D Spatial Reasoning by shifting from 2D pixel-relative grounding to depth-aware coordinate prediction and absolute metric constraint comprehension, generating complete 3D manipulation traces as ordered keypoint sequences under physical constraints. Complementing this spatial precision, the model establishes Dense Temporal Value Estimation that provides dense, step-aware progress prediction and execution state understanding across varying viewpoints, producing stable feedback signals for downstream learning. Together, these upgrades extend the framework toward more physically grounded and execution-aware embodied intelligence for complex, fine-grained manipulation. The code and checkpoints are available at project website: https://superrobobrain.github.io

Keywords

embodied AIspatiotemporal supervision3D spatial reasoningdepth-aware coordinate predictionmetric constraint comprehension3D manipulation tracestemporal value estimationstep-aware progress predictionexecution state understanding

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