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Main Authors: Zimmerman, Nicky, Sodano, Matteo
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.12362
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author Zimmerman, Nicky
Sodano, Matteo
author_facet Zimmerman, Nicky
Sodano, Matteo
contents Lifelong localization is crucial for enabling the autonomy of service robots. In this paper, we present an overview of our past research on long-term localization and mapping, exploiting geometric priors such as floor plans and integrating textual and semantic information. Our approach was validated on challenging sequences spanning over many months, and we released open source implementations.
format Preprint
id arxiv_https___arxiv_org_abs_2410_12362
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Human-Inspired Long-Term Indoor Localization in Human-Oriented Environment
Zimmerman, Nicky
Sodano, Matteo
Robotics
Lifelong localization is crucial for enabling the autonomy of service robots. In this paper, we present an overview of our past research on long-term localization and mapping, exploiting geometric priors such as floor plans and integrating textual and semantic information. Our approach was validated on challenging sequences spanning over many months, and we released open source implementations.
title Human-Inspired Long-Term Indoor Localization in Human-Oriented Environment
topic Robotics
url https://arxiv.org/abs/2410.12362