SOS-Match: Segmentation for Open-Set Robust Correspondence Search and Robot Localization in Unstructured Environments

arXiv:2401.04791v2 Announce Type: replace-cross
Abstract: We present SOS-Match, a novel framework for detecting and matching objects in unstructured environments. Our system consists of 1) a front-end mapping pipeline using a zero-shot segmentation model to extract object masks from images and track them across frames and 2) a frame alignment pipeline that uses the geometric consistency of object relationships to efficiently localize across a variety of conditions. We evaluate SOS-Match on the Batvik seasonal dataset which includes drone flights collected over …

arxiv cs.cv cs.ro environments localization match robot robust search segmentation set type unstructured