TAG-K combines greedy randomized Kaczmarz row selection with tail averaging to deliver faster convergence and noise robustness for online inertial parameter estimation in robotics.
Cafe-mpc: A cascaded-fidelity model predictive control framework with tuning-free whole-body control,
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TAG-K: Tail-Averaged Greedy Kaczmarz for Computationally Efficient and Performant Online Inertial Parameter Estimation
TAG-K combines greedy randomized Kaczmarz row selection with tail averaging to deliver faster convergence and noise robustness for online inertial parameter estimation in robotics.