# Infinigence AI, Tsinghua and AgiBot propose Collective Experience Learning (CEL), validated on 96 robots with 98.3% success rate

- Source: 3D视觉工坊 · 微信公众号
- Published: 2026-10-30T10:00:00.000Z
- RoboHot: https://robohot.news/en/items/zqb5b2uid3htn34c5j1ygi37g
- Original: https://mp.weixin.qq.com/s?__biz=MzU1MjY4MTA1MQ==&mid=2247752690&idx=1&sn=570e91724d086c299abfb80549241cca&chksm=faa8e33a9e484879401984320f009cba545b9abfb00d46caccb489abfab251e7ebee2ba3145f&scene=126&sessionid=1793355295#rd

## Summary

Infinigence AI, together with Tsinghua University and AgiBot, proposed the Collective Experience Learning (CEL) paradigm and completed prototype validation on 96 robots. In a phone packaging task, policies trained with CEL completed 120 tests on two robots of the same model that did not participate in training, with the success rate rising from 79.2% to 98.3%; when the number of robots participating in learning increased from 16 to 96, the test success rate rose from 86.7% to 98.3%.

## Why it matters

Fault-tolerant asynchronous training across a 96-robot real-machine cluster and failure-guided experience retrieval provide a reproducible system and scale-benefit data for Collective Experience Learning.