• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.145-154
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• 2009

For developing an Automation equipment in construction, it is a key issue to develop 3D modeling technology which can be used for automatically recognizing environmental objects. Recently, for the development of "Intelligent Excavating System(IES), a research developing the real-time 3D terrain modeling technology has been implemented from 2006 in Korea and a stereo vision system is selected as the optimum technology. However, as a result of performance tests implemented in various earth moving environment, the 3D images obtained by stereo vision included considerable noise. Therefore, in this study, for getting rid of the noise which is necessarily generated in stereo image matching, the noise elimination algorithm of stereo-vision images for 3D terrain modeling was developed. The consequence of this study is expected to be applicable in developing an automation equipments which are used in field environment.

• Journal of Drive and Control
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• v.21 no.1
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• pp.31-37
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• 2024

In this study, to prevent accidents in underground facilities during excavation, we developed a Lv.3 automated control system that can be configured as an electronic control system without changing the existing hydraulic system in a general excavator and utilized digital map information of underground facilities. We aimed to develop a strategy to prevent accidents caused by operator error. To implement this, a real-time excavator bucket end position recognition and control system was developed through angle measurement of the boom, arm, and bucket using an electronic joystick, RTK-GPS, and angle sensors. In addition, excavators are large, machine-based equipment, and it is difficult to control overshoot due to inertia with feedback control using position recognition information of the bucket tip. Therefore, feed-forward control is used to calculate the moving speed of the bucket tip in real-time to determine the target position. We developed a technology that can converge and verified the performance of the developed system through actual vehicle installation and field tests.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.1
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• pp.76-83
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• 2010

There have been many studies regarding development of autonomous excavation system which is helpful in construction sites where repetitive jobs are necessary. Unfortunately, bucket trajectory planning was excluded from the previous studies. Since, the best use of excavator is to dig efficiently; purpose of this research was set to determine an optimized bucket trajectory in order to get best digging performance. Among infinite ways of digging any given path, criterion for either optimal or efficient bucket moves is required to be established. One method is to adopt work know-how from experienced excavator operator; However the work pattern varies from every worker to worker and it is hard to be analyzed. Thus, other than the work pattern taken from experienced operator, we developed an efficiency model to solve this problem. This paper presents a method to derive a bucket trajectory from optimization theory with empirical CLUB soil model. Path is greatly influenced by physical constraints such as geometry, excavator dimension and excavator workspace. By minimizing a energy function under these constraints, an optimal bucket trajectory could be obtained.

• Korean Journal of Computational Design and Engineering
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• v.12 no.6
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• pp.405-412
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• 2007

It's difficult for manufacturers to derive a new design from the demands of consumers as quickly as possible and a designer carries out design operation using insufficient resources in initial design. To carry out initial design process efficiently for an excavator front group, it is necessary for a designer to manage lots of parameter with an existing knowledge or with in-house know-how and develop function module that calculates working range and excavator force. By doing so, it will bring up the optimized values of parameters based on the DOE in the early design stage. In this paper, a new approach to improve the process with optimized parameters is proposed to reduce a product development time of the excavator front design.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1609-1623
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• 2014

A number of studies have been conducted recently regarding the development of automation systems for the construction sector. Much of this attention has focused on earthwork because it is highly dependent on construction machines and is regarded as being basic for the construction of buildings and civil works. For example, technologies are being developed in order to enable earthwork planning based on construction site models that are constructed by automatic systems and to enable construction equipment to perform the work based on the plan and the environment. There are many problems that need to be solved in order to enable the use of automatic earthwork systems in construction sites. For example, technologies are needed for enabling collaborations between similar and different kinds of construction equipment. This study aims to develop a construction system that imitates collaborative systems and decision-making methods that are used by humans. The proposed system relies on the multi-agent concept from the field of artificial intelligence. In order to develop a multi-agent-based system, configurations and functions are proposed for the agents and a framework for collaboration and arbitration between agents is presented. Furthermore, methods are introduced for preventing duplicate work and minimizing interference effects during the collaboration process. Methods are also presented for performing advance planning for the excavators and compactors that are involved in the construction. The current study suggests a theoretical framework and evaluates the results using virtual simulations. However, in the future, an empirical study will be conducted in order to apply these concepts to actual construction sites through the development of a physical system.