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Tsinghua University, Infinigence AI, and AgiBot propose collective experience learning CEL, validated on a 96-robot cluster

Tsinghua University, Infinigence AI, and AgiBot jointly proposed the collective experience learning (CEL) paradigm, which lets robots share the successful experience of their peers rather than relying only on human demonstrations, and validated it on a cluster of 96 real robots. Two robots that did not participate in training were tested 600 times in total across five tasks—flower arranging, clothes folding, phone charging, stool assembly, and phone packaging—with 15 failures, for an overall success rate of 97.5%, all exceeding the average level of 6 human operators; the success rate on the phone packaging task rose from 79.2% to 98.3%.

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

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