Fast Ergodic Search with Kernel Functions

arXiv:2403.01536v1 Announce Type: cross
Abstract: Ergodic search enables optimal exploration of an information distribution while guaranteeing the asymptotic coverage of the search space. However, current methods typically have exponential computation complexity in the search space dimension and are restricted to Euclidean space. We introduce a computationally efficient ergodic search method. Our contributions are two-fold. First, we develop a kernel-based ergodic metric and generalize it from Euclidean space to Lie groups. We formally prove the proposed metric is consistent with the …

abstract arxiv complexity computation coverage cs.lg cs.ro current distribution exploration functions information kernel search space type