Training framework of the GAF-CNN model.

<div><p>In multi-robot collaboration, individual failures can propagate to other robots due to the topological coupling between them. Existing fault diagnosis models are designed for single robots and fail to meet the practical requirements of multi-robot scenarios. To address this, this...

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Номзүйн дэлгэрэнгүй
Үндсэн зохиолч:	Yan Qin (118276) (author)
Бусад зохиолчид:	Ouyang Wang (21772292) (author)
Хэвлэсэн:	2025
Нөхцлүүд:	Genetics Neuroscience Biotechnology Evolutionary Biology Ecology Cancer Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified potential knowledge shift incorporating group speed gramian angular field experimental results demonstrate robot &# 8217 group behavior consistency local fault datasets local model parameters individual robot training individual robot components based fault self federated learning framework federated learning local data fault models robot systems robot scenarios robot collaboration individual robots individual failures direction consistency shared learning proposed self collaborative self xlink "> trained using topological coupling study develops single robots robots due practical requirements multiple robots generate two frequency plots encoded using dimensional time different robots diagnosis model behavioral coherence
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Training framework of the GAF-CNN model.

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