Hierarchical localization with panoramic views and triplet loss functions

arXiv:2404.14117v1 Announce Type: cross
Abstract: The main objective of this paper is to address the mobile robot localization problem with Triplet Convolutional Neural Networks and test their robustness against changes of the lighting conditions. We have used omnidirectional images from real indoor environments captured in dynamic conditions that have been converted to panoramic format. Two approaches are proposed to address localization by means of triplet neural networks. First, hierarchical localization, which consists in estimating the robot position in two stages: …

abstract arxiv convolutional neural networks cs.ai cs.cv cs.ro dynamic environments functions hierarchical images lighting localization loss mobile networks neural networks paper robot robustness test type