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AgiBot and Tsinghua Release CEL Collective Experience Learning Paradigm, Achieving Autonomous Swarm Evolution with 96 Real Robots

AgiBot, together with Tsinghua University and Infinigence AI, released the collective experience learning paradigm CEL, which lets robots use the success and failure trajectories of their peers as learning material, with humans only responsible for judging outcomes. Across five real-world tasks—flower arranging, clothes folding, phone charging, stool assembly, and phone packaging—policies trained with CEL all exceeded the average level of 6 human teleoperators, leading by up to 16.7 percentage points; in the phone packaging task, the number of robots participating in training expanded from 16 to 96, and the success rate rose from 86.7% to 98.3%.

Part of the event: Tsinghua, Infinigence AI, and AgiBot propose CEL, validated on 96 robots

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