Tsinghua University, Wuwen Xinqiong, and Agibot Demonstrate Collective Experience Learning Paradigm on 96 Humanoid Robots
机器人互相“取经学习”!产学研联合提出具身智能规模化新方案
Tsinghua University, in collaboration with Wuwen Xinqiong and Agibot, demonstrated a new paradigm called Collective Experience Learning (CEL) for embodied intelligence. Validated across 96 humanoid robots, CEL allows machines to share experiences rather than relying solely on human instruction. In real-world tests involving five tasks such as flower arranging and phone packaging, the robot group achieved an overall success rate of 97.5%, exceeding the average performance of six human operators.
Source: Robotics — Chinese web discovery · 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
Reported success rate
97.5%
Reported trials
Reported success rate
98.3%
Reported trials
- paper: not_reported
What remains unknown
Not established in the collected evidence: Environment, Control, Data origin.
Reported performance applies to the described task. It does not establish general autonomy or deployment readiness.
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
近日,清华大学联合无问芯穹、智元推出群体经验学习(CEL)新范式,并且在96台真实人形 机器人 群体上完成验证。
Open source S2
经过群体学习训练,机器人群体整体任务成功率达到97.5%,五项任务的表现全部超过6名人类操作员的平均水平。
Open source S9
其中流程复杂的手机包装任务,成功率从79.2%提升至98.3%。
Open source S10
系统层面搭建容错异步训练系统FATS,即便出现网络波动、部分机器人硬件故障,近百台机器仍可持续协同训练,硬件故障带来的时间损耗仅占总运行时长1.3%。
Open source S13
实验还证实规模化效应:参与训练机器人由16台扩大到96台,整体能力随之进一步提升。
Open source S11
Source:Robotics — Chinese web discovery · finance.sina.com.cn