From Model Release to Production Line Validation: 2026 Embodied Large Model 'Real Power' Layered Map
从模型发布到产线验证：2026具身大模型“真实力”分层图谱
In 2026, embodied intelligence has moved beyond concept validation into scaled commercial deployment. The article evaluates the progress of domestic companies in deploying embodied large models, categorizing them into four layers based on their ability to pass through complete iteration paths, achieve multi-scenario replication, and comply with international regulations. It highlights AI²Robotics (智平方) as a leading example, showcasing its four-generation model development, cross-industry applications, and compliance in international markets.
Source: Chinese robotics — Robot learning research · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
collision response time
20
View original evidence
核心性能：碰撞后 20 毫秒安全反射（传统系统 > 200 毫秒），急动度峰值降低 80.2%，“脊髓”层功耗仅 0.4 瓦。
Open source S13peak jerk reduction
80.2
View original evidence
核心性能：碰撞后 20 毫秒安全反射（传统系统 > 200 毫秒），急动度峰值降低 80.2%，“脊髓”层功耗仅 0.4 瓦。
Open source S13spinal layer power consumption
0.4
View original evidence
核心性能：碰撞后 20 毫秒安全反射（传统系统 > 200 毫秒），急动度峰值降低 80.2%，“脊髓”层功耗仅 0.4 瓦。
Open source S13core component runtime
20,000–50,000 hours
View original evidence
自有产线年产能 2000 台，月出货超百台，核心部件无故障运行 2 万-5 万小时，2026 下半年启动国内首个数万台产线建设。
Open source S19
- paper: not_reported
- code: not_reported
- weights: not_reported
- dataset: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
核心性能：碰撞后 20 毫秒安全反射（传统系统 > 200 毫秒），急动度峰值降低 80.2%，“脊髓”层功耗仅 0.4 瓦。
Open source S13
第四代，2026 年 4 月发布全球第一个类脑架构 VLA 具身大模型 NeuroVLA，构建“皮层-小脑-脊髓”三层类脑体系，被学界认证为全球唯一同时具备主动感知、故障自恢复与时序记忆三大类生物运动能力的具身智能系统。
Open source S12
自有产线年产能 2000 台，月出货超百台，核心部件无故障运行 2 万-5 万小时，2026 下半年启动国内首个数万台产线建设。
Open source S19
Source：Chinese robotics — Robot learning research · ithome.com