Multi-modal Perception Dataset of In-water Objects for Autonomous Surface Vehicles

arXiv:2404.18411v1 Announce Type: cross
Abstract: This paper introduces the first publicly accessible multi-modal perception dataset for autonomous maritime navigation, focusing on in-water obstacles within the aquatic environment to enhance situational awareness for Autonomous Surface Vehicles (ASVs). This dataset, consisting of diverse objects encountered under varying environmental conditions, aims to bridge the research gap in marine robotics by providing a multi-modal, annotated, and ego-centric perception dataset, for object detection and classification. We also show the applicability of the proposed dataset's framework …

abstract arxiv autonomous bridge cs.cv cs.ro dataset diverse environment environmental modal multi-modal navigation objects obstacles paper perception situational awareness surface type vehicles water