Online Object-Oriented Semantic Mapping and Map Updating

Fuente: arXiv
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Main Authors: Dengler, Nils, Zaenker, Tobias, Verdoja, Francesco, Bennewitz, Maren
Format: Preprint
Published: 2020
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author Dengler, Nils
Zaenker, Tobias
Verdoja, Francesco
Bennewitz, Maren
author_facet Dengler, Nils
Zaenker, Tobias
Verdoja, Francesco
Bennewitz, Maren
contents Creating and maintaining an accurate representation of the environment is an essential capability for every service robot. Especially for household robots acting in indoor environments, semantic information is important. In this paper, we present a semantic mapping framework with modular map representations. Our system is capable of online mapping and object updating given object detections from RGB-D data and provides various 2D and 3D~representations of the mapped objects. To undo wrong data associations, we perform a refinement step when updating object shapes. Furthermore, we maintain an existence likelihood for each object to deal with false positive and false negative detections and keep the map updated. Our mapping system is highly efficient and achieves a run time of more than 10 Hz. We evaluated our approach in various environments using two different robots, i.e., a Toyota HSR and a Fraunhofer Care-O-Bot-4. As the experimental results demonstrate, our system is able to generate maps that are close to the ground truth and outperforms an existing approach in terms of intersection over union, different distance metrics, and the number of correct object mappings
format Preprint
id arxiv_https___arxiv_org_abs_2011_06895
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Online Object-Oriented Semantic Mapping and Map Updating
Dengler, Nils
Zaenker, Tobias
Verdoja, Francesco
Bennewitz, Maren
Robotics
Creating and maintaining an accurate representation of the environment is an essential capability for every service robot. Especially for household robots acting in indoor environments, semantic information is important. In this paper, we present a semantic mapping framework with modular map representations. Our system is capable of online mapping and object updating given object detections from RGB-D data and provides various 2D and 3D~representations of the mapped objects. To undo wrong data associations, we perform a refinement step when updating object shapes. Furthermore, we maintain an existence likelihood for each object to deal with false positive and false negative detections and keep the map updated. Our mapping system is highly efficient and achieves a run time of more than 10 Hz. We evaluated our approach in various environments using two different robots, i.e., a Toyota HSR and a Fraunhofer Care-O-Bot-4. As the experimental results demonstrate, our system is able to generate maps that are close to the ground truth and outperforms an existing approach in terms of intersection over union, different distance metrics, and the number of correct object mappings
title Online Object-Oriented Semantic Mapping and Map Updating
topic Robotics
url https://arxiv.org/abs/2011.06895