A neural-network latent-state friction model, trained by EM with particle filtering, predicts KUKA KR6 R700 open-loop dynamics more accurately than six baselines on a single validation trajectory.
Kim, ”Moment of inertia and friction torque coefficient identification in a servo drive system,” IEEE Transactions on Industrial Electronics , vol
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Probabilistic Latent Variable Modeling for Dynamic Friction Identification and Estimation
A neural-network latent-state friction model, trained by EM with particle filtering, predicts KUKA KR6 R700 open-loop dynamics more accurately than six baselines on a single validation trajectory.