Learning Optimal Topology for Ad-hoc Robot Networks

arXiv:2201.12900v2 Announce Type: replace-cross
Abstract: In this paper, we synthesize a data-driven method to predict the optimal topology of an ad-hoc robot network. This problem is technically a multi-task classification problem. However, we divide it into a class of multi-class classification problems that can be more efficiently solved. For this purpose, we first compose an algorithm to create ground-truth optimal topologies associated with various configurations of a robot network. This algorithm incorporates a complex collection of optimality criteria that our …

abstract arxiv class classification cs.lg cs.ro data data-driven however network networks paper robot topology type