Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning

The application of scene recognition in intelligent robots to forklift AGV equipment is of great significance in order to improve the automation and intelligence level of distribution centers. At present, using the camera to collect image information to obtain environmental information can break thr...

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Autores principales:	Gang Liu, Rongxu Zhang, Yanyan Wang, Rongjun Man
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	storage system forklift AGV deep learning semantic segmentation H-Swish Chemical technology TP1-1185 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/bcedc2e49896420da12fc333b57569a8
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id	oai:doaj.org-article:bcedc2e49896420da12fc333b57569a8
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spelling	oai:doaj.org-article:bcedc2e49896420da12fc333b57569a82021-11-25T18:50:44ZRoad Scene Recognition of Forklift AGV Equipment Based on Deep Learning10.3390/pr91119552227-9717https://doaj.org/article/bcedc2e49896420da12fc333b57569a82021-10-01T00:00:00Zhttps://www.mdpi.com/2227-9717/9/11/1955https://doaj.org/toc/2227-9717The application of scene recognition in intelligent robots to forklift AGV equipment is of great significance in order to improve the automation and intelligence level of distribution centers. At present, using the camera to collect image information to obtain environmental information can break through the limitation of traditional guideway and positioning equipment, and is beneficial to the path planning and system expansion in the later stage of warehouse construction. Taking the forklift AGV equipment in the distribution center as the research object, this paper explores the scene recognition and path planning of forklift AGV equipment based on a deep convolution neural network. On the basis of the characteristics of the warehouse environment, a semantic segmentation network applied to the scene recognition of the warehouse environment is established, and a scene recognition method suitable for the warehouse environment is proposed, so that the equipment can use the deep learning method to learn the environment features and achieve accurate recognition in the large-scale environment, without adding environmental landmarks, which provides an effective convolution neural network model for the scene recognition of forklift AGV equipment in the warehouse environment. The activation function layer of the model is studied by using the activation function with better gradient performance. The results show that the performance of the H-Swish activation function is better than that of the ReLU function in recognition accuracy and computational complexity, and it can save costs as a calculation form of the mobile terminal.Gang LiuRongxu ZhangYanyan WangRongjun ManMDPI AGarticlestorage systemforklift AGVdeep learningsemantic segmentationH-SwishChemical technologyTP1-1185ChemistryQD1-999ENProcesses, Vol 9, Iss 1955, p 1955 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	storage system forklift AGV deep learning semantic segmentation H-Swish Chemical technology TP1-1185 Chemistry QD1-999
spellingShingle	storage system forklift AGV deep learning semantic segmentation H-Swish Chemical technology TP1-1185 Chemistry QD1-999 Gang Liu Rongxu Zhang Yanyan Wang Rongjun Man Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning
description	The application of scene recognition in intelligent robots to forklift AGV equipment is of great significance in order to improve the automation and intelligence level of distribution centers. At present, using the camera to collect image information to obtain environmental information can break through the limitation of traditional guideway and positioning equipment, and is beneficial to the path planning and system expansion in the later stage of warehouse construction. Taking the forklift AGV equipment in the distribution center as the research object, this paper explores the scene recognition and path planning of forklift AGV equipment based on a deep convolution neural network. On the basis of the characteristics of the warehouse environment, a semantic segmentation network applied to the scene recognition of the warehouse environment is established, and a scene recognition method suitable for the warehouse environment is proposed, so that the equipment can use the deep learning method to learn the environment features and achieve accurate recognition in the large-scale environment, without adding environmental landmarks, which provides an effective convolution neural network model for the scene recognition of forklift AGV equipment in the warehouse environment. The activation function layer of the model is studied by using the activation function with better gradient performance. The results show that the performance of the H-Swish activation function is better than that of the ReLU function in recognition accuracy and computational complexity, and it can save costs as a calculation form of the mobile terminal.
format	article
author	Gang Liu Rongxu Zhang Yanyan Wang Rongjun Man
author_facet	Gang Liu Rongxu Zhang Yanyan Wang Rongjun Man
author_sort	Gang Liu
title	Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning
title_short	Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning
title_full	Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning
title_fullStr	Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning
title_full_unstemmed	Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning
title_sort	road scene recognition of forklift agv equipment based on deep learning
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bcedc2e49896420da12fc333b57569a8
work_keys_str_mv	AT gangliu roadscenerecognitionofforkliftagvequipmentbasedondeeplearning AT rongxuzhang roadscenerecognitionofforkliftagvequipmentbasedondeeplearning AT yanyanwang roadscenerecognitionofforkliftagvequipmentbasedondeeplearning AT rongjunman roadscenerecognitionofforkliftagvequipmentbasedondeeplearning
_version_	1718410673222844416

Road Scene Recognition of Forklift AGV Equipment Based on Deep Learning

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