A Bayesian optimization method with heteroscedastic Gaussian process surrogate and movement switching cost achieves sublinear regret and effective source localization in simulations for radioactive source seeking.
Performance improvement and limitations in extremum seeking control
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Radioactive Source Seeking using Bayesian Optimisation with Movement Penalty
A Bayesian optimization method with heteroscedastic Gaussian process surrogate and movement switching cost achieves sublinear regret and effective source localization in simulations for radioactive source seeking.