4D modeling of soil surface during excavation using a solid-state 2D profilometer mounted on the arm of an excavator

Niskanen, Ilpo; Immonen, Matti; Makkonen, Teemu; Keränen, Pekka; Tyni, Pekka; Hallman, Lauri; Hiltunen, Mikko; Kolli, Tanja; Louhisalmi, Y.; Kostamovaara, J.; Heikkilä, Rauno

doi:10.1016/j.autcon.2020.103112

Cited by 21 publications

(7 citation statements)

References 14 publications

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“…Our previous work studied the measurement of a soil surface profile using an excavator (Niskanen et al 2020). The experimental results were encouraging and demonstrated the profilometer's good ground surface visualisation performance.…”

Section: Introductionmentioning

confidence: 91%

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Trench visualisation from a semiautonomous excavator with a base grid map using a TOF 2D profilometer

Niskanen

Immonen

Makkonen

et al. 2023

J Vis

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Real-time, three-dimensional (3D) visualisation technology can be used at construction sites to improve the quality of work. A 3D view of the landscape under work can be compared to a target 3D model of the landscape to conveniently show needed excavation tasks to a human excavator operator or to show the progress of an autonomous excavator. The purpose of this study was to demonstrate surface visualisation from measurements taken with a pulsed time-of-flight (TOF) 2D profilometer on-board a semiautonomous excavator. The semiautomatic excavator was implemented by recording the feedback script parameters from the work performed on the excavator by a human driver. 3D visualisation maps based on the triangle mesh technique were generated from the 3D point cloud using measurements of the trenches dug by a human and an autonomous excavator. The accuracy of the 3D maps was evaluated by comparing them to a high-resolution commercial 3D scanner. An analysis of the results shows that the 2D profilometer attached to the excavator can achieve almost the same 3D results as a high-quality on-site static commercial 3D scanner, whilst more easily providing an unobstructed view of the trench during operation (a 3D scanner placed next to a deep trench might not have a full view of the trench). The main technical advantages of our 2D profilometer are its compact size, measurement speed, lack of moving parts, robustness, low-cost technology that enables visualisations from a unique viewpoint on the boom of the excavator, and readiness for real-time control of the excavator’s system. This research is expected to encourage the efficiency of the digging process in the future, as well as to provide a remarkable view of trench work using an excavator as a moving platform to facilitate data visualisation. Graphical abstract

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Section: Introductionmentioning

confidence: 91%

“…where u offset is the angle between the scanner and the excavator's boom. More information on the calculation routine can be found in Niskanen et al (2020).…”

Section: Theorymentioning

confidence: 99%

Trench visualisation from a semiautonomous excavator with a base grid map using a TOF 2D profilometer

Niskanen

Immonen

Makkonen

et al. 2023

J Vis

Self Cite

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“…Although the stereo camera provides the geometrical data for a 3D map, this data is not sufficient to capture other crucial info of excavation materials that can be represented by the beam reflectivity or intensity [ 21 ]. To fuse the reflectivity info with the 3D map, we applied the intensity data from a LiDAR sensor as an index for the identification of material types [ 12 ]. This is because since the LiDAR can generate the intensity data used for numerous applications, such as wet area identification, land cover classification, distinguishing features, etc.…”

Section: 5d Mappingmentioning

confidence: 99%

“…The commonly used sensor combination for 3D navigation and estimation of the ground surface in excavators includes the inertial measurement unit (IMU) fused with GPS or GNSS. Using the joint angle data obtained from this configuration and kinematic information, the dynamic status of an excavator was estimated, which can be further utilized for the estimation of a 3D profile of ground surface [ 11 , 12 ]. The stereo vision (depth camera)-based methodology has been utilized to identify the ground surface including rock piles [ 13 ] through stereo matching in the left and right images that allows obtaining the depth images of the surface.…”

Section: Introductionmentioning

confidence: 99%

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Development of Integrative Methodologies for Effective Excavation Progress Monitoring

Abdullah

Seo

Khajepour

2021

Sensors

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Excavation is one of the primary projects in the construction industry. Introducing various technologies for full automation of the excavation can be a solution to improve sensing and productivity that are the ongoing issues in this area. This paper covers three aspects of effective excavation progress monitoring that include excavation volume estimation, occlusion area detection, and 5D mapping. The excavation volume estimation component enables estimating the bucket volume and ground excavation volume. To achieve mapping of the hidden or occluded ground areas, integration of proprioceptive and exteroceptive sensing data was adopted. Finally, we proposed the idea of 5D mapping that provides the info of the excavated ground in terms of geometric space and material type/properties using a 3D ground map with LiDAR intensity and a ground resistive index. Through experimental validations with a mini excavator, the accuracy of the two different volume estimation methods was compared. Finally, a reconstructed map for occlusion areas and a 5D map were created using the bucket tip’s trajectory and multiple sensory data with convolutional neural network techniques, respectively. The created 5D map would allow for the provision of extended ground information beyond a normal 3D ground map, which is indispensable to progress monitoring and control of autonomous excavation.

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Comparison of Exhaust Gas Emissions Between Autonomous and Human Operator Excavator

Kolli

Hiltunen

Niskanen

et al. 2023

Sustainable and Digital Building

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4D modeling of soil surface during excavation using a solid-state 2D profilometer mounted on the arm of an excavator

Cited by 21 publications

References 14 publications

Trench visualisation from a semiautonomous excavator with a base grid map using a TOF 2D profilometer

Trench visualisation from a semiautonomous excavator with a base grid map using a TOF 2D profilometer

Development of Integrative Methodologies for Effective Excavation Progress Monitoring

Comparison of Exhaust Gas Emissions Between Autonomous and Human Operator Excavator

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