Wide-range sediment volume estimation by pointclouds from multiple viewpoints for soil loading task

In Japan, “i-Construction” is promoted to improve the productivity of the construction industries by utilizing Information and Communication Technology (ICT). In particular, estimation of sediment volume at construction sites is highly demanded, for example, in order to pre-order the number of truck...

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Main Authors: Kenta KAWAMATA, Hiromitsu FUJII, Yuta HATAKEYAMA, Masato DOMAE, Takaaki MORIMOTO, Takeya IZUMIKAWA
Format: Article
Language:Japanese
Published: The Japan Society of Mechanical Engineers 2021-06-01
Series:Nihon Kikai Gakkai ronbunshu
Subjects:
Online Access:https://www.jstage.jst.go.jp/article/transjsme/87/898/87_20-00122/_pdf/-char/en
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author Kenta KAWAMATA
Hiromitsu FUJII
Yuta HATAKEYAMA
Masato DOMAE
Takaaki MORIMOTO
Takeya IZUMIKAWA
author_facet Kenta KAWAMATA
Hiromitsu FUJII
Yuta HATAKEYAMA
Masato DOMAE
Takaaki MORIMOTO
Takeya IZUMIKAWA
author_sort Kenta KAWAMATA
collection DOAJ
description In Japan, “i-Construction” is promoted to improve the productivity of the construction industries by utilizing Information and Communication Technology (ICT). In particular, estimation of sediment volume at construction sites is highly demanded, for example, in order to pre-order the number of trucks correctly. In current construction sites, the sediment volume is calculated based on conventional terrain measurement methods by using special survey instruments such as a total station. These kinds of methods, however, need a lot of time and manpower. In this paper, we propose a method that estimates sediment volume more easily from three-dimensional (3D) pointcloud data obtained by only sensors installed on a backhoe. Our system is consisted of a LiDAR for 3D shape measurement and a tracking sensor for movement measurement by visual odometry. To obtain dense point clouds, the LiDAR of our system is rotative on a pan-tilt (PT) unit, whose relative relationship between both coordinate systems of LiDAR and the PT unit is estimated beforehand by our calibration method. At construction sites, the backhoe mounting our sensing system measures a ground surface from multiple viewpoints during movement, and a batch of 3D pointclouds of a wide range is integrated by a registration technique. From the whole pointcloud, the sediment volume on the ground can be estimated. In an outdoor experiment, we validated effectiveness of our proposed method by evaluating the accuracy of the estimation results.
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spelling doaj.art-a995006f29424770834abfa4a72589aa2022-12-22T02:52:23ZjpnThe Japan Society of Mechanical EngineersNihon Kikai Gakkai ronbunshu2187-97612021-06-018789820-0012220-0012210.1299/transjsme.20-00122transjsmeWide-range sediment volume estimation by pointclouds from multiple viewpoints for soil loading taskKenta KAWAMATA0Hiromitsu FUJII1Yuta HATAKEYAMA2Masato DOMAE3Takaaki MORIMOTO4Takeya IZUMIKAWA5Chiba Institute of TechnologyChiba Institute of TechnologyChiba Institute of TechnologyChiba Institute of TechnologySumitomo Construction Machinery Co., Ltd.Sumitomo Construction Machinery Co., Ltd.In Japan, “i-Construction” is promoted to improve the productivity of the construction industries by utilizing Information and Communication Technology (ICT). In particular, estimation of sediment volume at construction sites is highly demanded, for example, in order to pre-order the number of trucks correctly. In current construction sites, the sediment volume is calculated based on conventional terrain measurement methods by using special survey instruments such as a total station. These kinds of methods, however, need a lot of time and manpower. In this paper, we propose a method that estimates sediment volume more easily from three-dimensional (3D) pointcloud data obtained by only sensors installed on a backhoe. Our system is consisted of a LiDAR for 3D shape measurement and a tracking sensor for movement measurement by visual odometry. To obtain dense point clouds, the LiDAR of our system is rotative on a pan-tilt (PT) unit, whose relative relationship between both coordinate systems of LiDAR and the PT unit is estimated beforehand by our calibration method. At construction sites, the backhoe mounting our sensing system measures a ground surface from multiple viewpoints during movement, and a batch of 3D pointclouds of a wide range is integrated by a registration technique. From the whole pointcloud, the sediment volume on the ground can be estimated. In an outdoor experiment, we validated effectiveness of our proposed method by evaluating the accuracy of the estimation results.https://www.jstage.jst.go.jp/article/transjsme/87/898/87_20-00122/_pdf/-char/enexcavator operationvisual odometrylidarpointcloudregistrationvoxelizationvolume estimation
spellingShingle Kenta KAWAMATA
Hiromitsu FUJII
Yuta HATAKEYAMA
Masato DOMAE
Takaaki MORIMOTO
Takeya IZUMIKAWA
Wide-range sediment volume estimation by pointclouds from multiple viewpoints for soil loading task
Nihon Kikai Gakkai ronbunshu
excavator operation
visual odometry
lidar
pointcloud
registration
voxelization
volume estimation
title Wide-range sediment volume estimation by pointclouds from multiple viewpoints for soil loading task
title_full Wide-range sediment volume estimation by pointclouds from multiple viewpoints for soil loading task
title_fullStr Wide-range sediment volume estimation by pointclouds from multiple viewpoints for soil loading task
title_full_unstemmed Wide-range sediment volume estimation by pointclouds from multiple viewpoints for soil loading task
title_short Wide-range sediment volume estimation by pointclouds from multiple viewpoints for soil loading task
title_sort wide range sediment volume estimation by pointclouds from multiple viewpoints for soil loading task
topic excavator operation
visual odometry
lidar
pointcloud
registration
voxelization
volume estimation
url https://www.jstage.jst.go.jp/article/transjsme/87/898/87_20-00122/_pdf/-char/en
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AT hiromitsufujii widerangesedimentvolumeestimationbypointcloudsfrommultipleviewpointsforsoilloadingtask
AT yutahatakeyama widerangesedimentvolumeestimationbypointcloudsfrommultipleviewpointsforsoilloadingtask
AT masatodomae widerangesedimentvolumeestimationbypointcloudsfrommultipleviewpointsforsoilloadingtask
AT takaakimorimoto widerangesedimentvolumeestimationbypointcloudsfrommultipleviewpointsforsoilloadingtask
AT takeyaizumikawa widerangesedimentvolumeestimationbypointcloudsfrommultipleviewpointsforsoilloadingtask