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Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception

In this paper, we propose an end-to-end automatic walking system for construction machinery, which uses binocular cameras to capture images of construction machinery for environmental perception, detects target information in binocular images, estimates the relative distance between the current targ...

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Detalles Bibliográficos
Autores principales: Fang, Zhen, Lin, Tianliang, Li, Zhongshen, Yao, Yu, Zhang, Chunhui, Ma, Ronghua, Chen, Qihuai, Fu, Shengjie, Ren, Haoling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147558/
https://www.ncbi.nlm.nih.gov/pubmed/35630138
http://dx.doi.org/10.3390/mi13050671
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author Fang, Zhen
Lin, Tianliang
Li, Zhongshen
Yao, Yu
Zhang, Chunhui
Ma, Ronghua
Chen, Qihuai
Fu, Shengjie
Ren, Haoling
author_facet Fang, Zhen
Lin, Tianliang
Li, Zhongshen
Yao, Yu
Zhang, Chunhui
Ma, Ronghua
Chen, Qihuai
Fu, Shengjie
Ren, Haoling
author_sort Fang, Zhen
collection PubMed
description In this paper, we propose an end-to-end automatic walking system for construction machinery, which uses binocular cameras to capture images of construction machinery for environmental perception, detects target information in binocular images, estimates the relative distance between the current target and cameras, and predicts the real-time control signal of construction machinery. This system consists of two parts: the binocular recognition ranging model and the control model. Objects within 5 m can be quickly detected by the recognition ranging model, and at the same time, the distance of the object can be accurately ranged to ensure the full perception of the surrounding environment of the construction machinery. The distance information of the object, the feature information of the binocular image, and the control signal of the previous stage are sent to the control model; then, the prediction of the control signal of the construction machinery can be output in the next stage. In this way, the automatic walking experiment of the construction machinery in a specific scenario is completed, which proves that the model can control the machinery to complete the walking task smoothly and safely.
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spelling pubmed-91475582022-05-29 Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception Fang, Zhen Lin, Tianliang Li, Zhongshen Yao, Yu Zhang, Chunhui Ma, Ronghua Chen, Qihuai Fu, Shengjie Ren, Haoling Micromachines (Basel) Article In this paper, we propose an end-to-end automatic walking system for construction machinery, which uses binocular cameras to capture images of construction machinery for environmental perception, detects target information in binocular images, estimates the relative distance between the current target and cameras, and predicts the real-time control signal of construction machinery. This system consists of two parts: the binocular recognition ranging model and the control model. Objects within 5 m can be quickly detected by the recognition ranging model, and at the same time, the distance of the object can be accurately ranged to ensure the full perception of the surrounding environment of the construction machinery. The distance information of the object, the feature information of the binocular image, and the control signal of the previous stage are sent to the control model; then, the prediction of the control signal of the construction machinery can be output in the next stage. In this way, the automatic walking experiment of the construction machinery in a specific scenario is completed, which proves that the model can control the machinery to complete the walking task smoothly and safely. MDPI 2022-04-25 /pmc/articles/PMC9147558/ /pubmed/35630138 http://dx.doi.org/10.3390/mi13050671 Text en © 2022 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
Fang, Zhen
Lin, Tianliang
Li, Zhongshen
Yao, Yu
Zhang, Chunhui
Ma, Ronghua
Chen, Qihuai
Fu, Shengjie
Ren, Haoling
Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception
title Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception
title_full Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception
title_fullStr Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception
title_full_unstemmed Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception
title_short Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception
title_sort automatic walking method of construction machinery based on binocular camera environment perception
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147558/
https://www.ncbi.nlm.nih.gov/pubmed/35630138
http://dx.doi.org/10.3390/mi13050671
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