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Mushroom Detection and Three Dimensional Pose Estimation from Multi-View Point Clouds

Agricultural robotics is an up and coming field which deals with the development of robotic systems able to tackle a multitude of agricultural tasks efficiently. The case of interest, in this work, is mushroom collection in industrial mushroom farms. Developing such a robot, able to select and out-r...

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Autores principales: Retsinas, George, Efthymiou, Niki, Anagnostopoulou, Dafni, Maragos, Petros
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099271/
https://www.ncbi.nlm.nih.gov/pubmed/37050635
http://dx.doi.org/10.3390/s23073576
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author Retsinas, George
Efthymiou, Niki
Anagnostopoulou, Dafni
Maragos, Petros
author_facet Retsinas, George
Efthymiou, Niki
Anagnostopoulou, Dafni
Maragos, Petros
author_sort Retsinas, George
collection PubMed
description Agricultural robotics is an up and coming field which deals with the development of robotic systems able to tackle a multitude of agricultural tasks efficiently. The case of interest, in this work, is mushroom collection in industrial mushroom farms. Developing such a robot, able to select and out-root a mushroom, requires delicate actions that can only be conducted if a well-performing perception module exists. Specifically, one should accurately detect the 3D pose of a mushroom in order to facilitate the smooth operation of the robotic system. In this work, we develop a vision module for 3D pose estimation of mushrooms from multi-view point clouds using multiple RealSense active–stereo cameras. The main challenge is the lack of annotation data, since 3D annotation is practically infeasible on a large scale. To address this, we developed a novel pipeline for mushroom instance segmentation and template matching, where a 3D model of a mushroom is the only data available. We evaluated, quantitatively, our approach over a synthetic dataset of mushroom scenes, and we, further, validated, qualitatively, the effectiveness of our method over a set of real data, collected by different vision settings.
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spelling pubmed-100992712023-04-14 Mushroom Detection and Three Dimensional Pose Estimation from Multi-View Point Clouds Retsinas, George Efthymiou, Niki Anagnostopoulou, Dafni Maragos, Petros Sensors (Basel) Article Agricultural robotics is an up and coming field which deals with the development of robotic systems able to tackle a multitude of agricultural tasks efficiently. The case of interest, in this work, is mushroom collection in industrial mushroom farms. Developing such a robot, able to select and out-root a mushroom, requires delicate actions that can only be conducted if a well-performing perception module exists. Specifically, one should accurately detect the 3D pose of a mushroom in order to facilitate the smooth operation of the robotic system. In this work, we develop a vision module for 3D pose estimation of mushrooms from multi-view point clouds using multiple RealSense active–stereo cameras. The main challenge is the lack of annotation data, since 3D annotation is practically infeasible on a large scale. To address this, we developed a novel pipeline for mushroom instance segmentation and template matching, where a 3D model of a mushroom is the only data available. We evaluated, quantitatively, our approach over a synthetic dataset of mushroom scenes, and we, further, validated, qualitatively, the effectiveness of our method over a set of real data, collected by different vision settings. MDPI 2023-03-29 /pmc/articles/PMC10099271/ /pubmed/37050635 http://dx.doi.org/10.3390/s23073576 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Retsinas, George
Efthymiou, Niki
Anagnostopoulou, Dafni
Maragos, Petros
Mushroom Detection and Three Dimensional Pose Estimation from Multi-View Point Clouds
title Mushroom Detection and Three Dimensional Pose Estimation from Multi-View Point Clouds
title_full Mushroom Detection and Three Dimensional Pose Estimation from Multi-View Point Clouds
title_fullStr Mushroom Detection and Three Dimensional Pose Estimation from Multi-View Point Clouds
title_full_unstemmed Mushroom Detection and Three Dimensional Pose Estimation from Multi-View Point Clouds
title_short Mushroom Detection and Three Dimensional Pose Estimation from Multi-View Point Clouds
title_sort mushroom detection and three dimensional pose estimation from multi-view point clouds
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099271/
https://www.ncbi.nlm.nih.gov/pubmed/37050635
http://dx.doi.org/10.3390/s23073576
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