Feature Based Modeling and Mapping of Tree Trunks and Natural Terrain Using 3D Laser Scanner Measurement System

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Hyyti, Heikki
dc.contributor.author Visala, Arto
dc.date.accessioned 2015-01-21T10:00:16Z
dc.date.available 2015-01-21T10:00:16Z
dc.date.issued 2013
dc.identifier.citation Hyyti, Heikki & Visala, Arto. 2013. Feature Based Modeling and Mapping of Tree Trunks and Natural Terrain Using 3D Laser Scanner Measurement System. 8th IFAC Symposium on Intelligent Autonomous Vehicles, Australia, 2013. Intelligent Autonomous Vehicles. Volume 8, Part 1. P. 248-255. DOI: 10.3182/20130626-3-AU-2035.00065. en
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/14990
dc.description.abstract This paper presents a novel approach to measure tree trunks and to model the ground using a 3D laser scanner. The 3D scanner, self-build using two 2D Sick scanners on a rotating base, measures each scan line approximately at 45° angle towards the ground and the trees. Single scan lines are segmented to find ground and tree returns. 3D point clouds from the surrounding forest are recorded while the measuring vehicle is moving. Sequential scan lines are joined together as the pose changes are reduced from the older buffered measurements. Laser odometry and inertial measurements are used to measure the pose changes. The ground is modeled by fitting a 1m grid to 3D point cloud extracted using a ground return detector. Tree trunks are searched from the 3D point cloud using a histogram approach to segment measurements into separate point clouds for each tree trunk. Tree trunks are modeled using ten circle features one on the other using the extracted point cloud. Instead of using the whole point cloud, mapping is done only for the extracted features and the travelled path to save computation time. Our method can detect nearly all tree trunks and measure them on short ranges of less than 8m with errors less than 4cm in diameter. en
dc.format.extent 248-255
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher IFAC en
dc.relation.ispartof 8th IFAC Symposium on Intelligent Autonomous Vehicles, Australia, 2013 en
dc.relation.ispartofseries Intelligent Autonomous Vehicles en
dc.relation.ispartofseries Volume 8, Part 1
dc.subject.other Automation en
dc.subject.other Computer science en
dc.title Feature Based Modeling and Mapping of Tree Trunks and Natural Terrain Using 3D Laser Scanner Measurement System en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed en
dc.rights.holder IFAC
dc.contributor.school Sähkötekniikan korkeakoulu fi
dc.contributor.school School of Electrical Engineering en
dc.contributor.department Automaatio- ja systeemitekniikan laitos fi
dc.contributor.department Department of Automation and Systems Technology en
dc.subject.keyword machine perception en
dc.subject.keyword laser scanning en
dc.subject.keyword 3D LIDAR en
dc.subject.keyword mobile mapping en
dc.subject.keyword tree detection en
dc.identifier.urn URN:NBN:fi:aalto-201501221180
dc.type.dcmitype text en
dc.identifier.doi 10.3182/20130626-3-AU-2035.00065
dc.contributor.lab Autonomous systems en
dc.contributor.lab Autonomiset järjestelmät fi
dc.type.version Post print en


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