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
RoboBrain 2.5: Depth in Sight, Time in Mind
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.
- Year
- 2026
- Venue
- arXiv 2026
- Stars
- 1.1k
- Authors
- 35
- Hosting
- Abstract onlyARXIV-DEFAULT
Cite
Notes
Only stored in your browser.
Attribution
- Abstract & full text
- arxiv.org/abs/2601.14352ARXIV-DEFAULT
- TL;DR
- Semantic Scholar
Abstract
Authors
35Zhiyu LiZhongyuan WangShanghang ZhangHuajie TanEnshen ZhouYijie XuYuheng JiXiansheng ChenCheng ChiPengwei WangHuizhu JiaYulong AoMingyu CaoSixiang ChenZhe LiMengzhen LiuZixiao WangShanyu RongYaoxu LyuZhongxia ZhaoPeterson CoYibo LiYi HanShaoxuan XieGuocai YaoSongjing WangLeiduo ZhangXi YangYance JiaoDonghai ShiKunchang XieShaokai NieChunlei MenYonghua LinTiejun Huang