• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.669-670
• /
• 2015

Efficient management of the construction heavy equipment is required to reduce the rate of carbon emissions and on-site accidents. The intelligent excavation system (IES) will improve the construction quality and productivity through information technologies and efficient equipment operation, especially in large earthwork projects. Three-dimensional digitized ground data should be required for identifying the path of heavy equipment and work-site environment. Rapid development of terrain laser scanners (TLS) is more readily to acquire the digital data. This study suggests the '3D ground terrain processing platform (3DGTPP)' including data manipulating module and analyzing module of the scanned data for intelligent earthmoving equipment operation. The processing platform consists of six modules, including scanning, registering, manipulating, analyzing, transmitting, and storing. 3D ground terrain processing platform presented in this study will provide fundamental information for intelligent excavation system (IES), which will increase the efficiency of earthworks and safety of workers in significant.

• Journal of Drive and Control
• /
• v.20 no.4
• /
• pp.133-139
• /
• 2023

A weighing system calculates the bucket's excavation amount of an excavator. Usually, the excavation amount is computed by the excavator's motion equations with sensing data. But these motion equations have computing errors that are induced by assumptions to the linear systems and identification of the equation's parameters. To reduce computing errors, some commercial weighing system incorporates particular motion into the excavation process. This study introduces a linear regression model on an artificial neural network that has fewer predicted errors and doesn't need a particular pose during an excavation. Time serial data were gathered from a 30tons excavator's loading test. Then these data were preprocessed to be adjusted by MPL (Multi Layer Perceptron) or CNN (Convolutional Neural Network) based linear regression models. Each model was trained by changing hyperparameter such as layer or node numbers, drop-out rate, and kernel size. Finally ID-CNN-based linear regression model was selected.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.3D
• /
• pp.269-274
• /
• 2012

A study on automation system for construction industry has been conducted for decades. However, performance evaluation of automation system has not been suggested yet. The performance evaluation has been conducted only for partial technical elements or for benefits gained through the introduction. This study develops a framework to evaluate the performance of intelligent excavation system in terms of economic feasibility and benefit, and presents a performance evaluation method for automation equipments. The applicability of intelligent excavation system on a site is also analyzed in this study.

• Journal of KIBIM
• /
• v.1 no.1
• /
• pp.1-5
• /
• 2011

Earthwork is important in terms of construction time and duration, and highly related to the construction productivity. However, current earthwork system has stick to labor intensive process depending on skilled operator's heuristic decision making, so it is hard to improve overall productivity. To overcome this drawback, this paper presents a BIM based Intelligent Excavation System(IES). The BIM technology is applied in the excavation task planning system, Human-Machine Interface for remote-control/autonomous work environment, and web-based Project Management Information System(PMIS) in the IES integration process, and the results are addressed.

• Proceedings of the Korean Geotechical Society Conference
• /
• 1997.10a
• /
• pp.141-150
• /
• 1997

• Journal of Drive and Control
• /
• v.5 no.2
• /
• pp.12-16
• /
• 2008

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.3D
• /
• pp.259-267
• /
• 2012

The development of construction automation systems is proposed as a potent solution to the difficulties encountered by the construction industry and the preparation for the rapidly changing construction environment. A research concerning an intelligent excavation system has taken place since 2006. The intelligent excavation system has several functions for environment sensing, 3D site modeling, work planning, work path generation, unmaned control, and information management. This paper presents a space information model and a work path simulator for work planning and work path generation which is one of key technologies required to apply the earthwork system to the real world. A data structure for an earthwork site is suggested. It overcomes the limitations of previous data structures such as Quadtree and Octree. The work path simulator can generate an effective work path with considering information on work environment, equipment and operator's heuristic. The work path generated by the simulator is compared with that suggested by human operators.

• Korean Journal of Construction Engineering and Management
• /
• v.10 no.1
• /
• pp.136-145
• /
• 2009

The objective of the Intelligent Excavation System (IES) is to recognize the work environment and produce work plan and automatically control the excavator through integrating sensor and robot technologies. This paper discusses one of the core technologies of IES development project, development of 3D work environment modeling. 3D laser scanner is used for 3-dimensional mathematical model that can be visualized in virtual space in 3D. This paper describes (1) how the most appropriate 3D imaging system has been chosen; (2) the development of user interface and customization of the s/w to control the scanner for IES project; (3) the development of the mobile station for the scanner; (4) and the algorithm for the automatic registration of laser scan segments for IES project. The development system has been tested on the construction field and lessons learned and future development requirements are suggested.

• Korean Journal of Construction Engineering and Management
• /
• v.12 no.6
• /
• pp.130-141
• /
• 2011

The intelligent excavating system(IES), the development in South Korea of which has been underway since 2006, aims for the full-scale automation of the excavation process that includes a series of tasks such as movement, excavation and loading. The core elements to ensure the quality and safety of the automated excavation equipment include 3D modeling of terrain that surrounds the excavating robot and the technology for detecting objects accurately(i.e., for detecting the location of nearby loading trucks and humans as well as of obstacles positioned on the movement paths). Therefore the purpose of this research is to ensure the quality and safety of automated excavation detecting the objects surrounding the excavating robot via a 3D laser scanning system. In this paper, an algorithm for estimating the location, height, width, and shape of objects in the 3D-realized terrain that surrounds the location of the excavator was proposed. The performance of the algorithm was verified via tests in an actual earthwork field.

• Journal of the Korea Institute of Building Construction
• /
• v.10 no.4
• /
• pp.105-112
• /
• 2010

The demand for the development of automated construction equipments is gradually increasing to deal with the current problems of construction technology, such as a lack of experienced workers, the aging of engineers, safety issues, etc. In particular, earth work such as excavation is very machine-dependent, and there has been a great deal of research on the development of an intelligent excavator, which involves great safety concerns. Thus, the objective of this study is to develop the technology to enhance the safety of intelligent excavation systems by developing an omnidirectional object detection technology for the intelligent excavator and applying it to a user-friendly system. The existing literature was reviewed, and the function of various sensor technologies was investigated and analyzed. Then, the best laser sensor was selected for an experiment to determine its effectiveness. An omnidirectional object detection algorithm was developed for a user interface program, and this can be used as the fundamental technology for the development of a safety management system for an intelligent excavator.