• Journal of the Korean Society for Precision Engineering
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• v.17 no.9
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• pp.32-38
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• 2000

• Proceedings of the KWS Conference
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• 2006.10a
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• pp.101-103
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• 2006

DSME has developed Sub-assembly Welding Robot System(SWRS) in order to increase the productivity of arc welding and to improve hazard and unclean environments in shipbuilding. DSME's SWRS includes a number of equipments such as four overhanging 6-axis articulated robot manipulators(10kg pay-load), gantry system, vision system detecting the workpiece automatically, and OLP system using the CAD data and a central control system integrating an anti-collision module. The SWRS was installed in CAS(Component Assembly Shop) of DSME's OKPO shipyard in August 2006, and now SWRS is running well in site.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.124-132
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• 2001

Autonomous of welding process in shipyard is ultimately necessary., since welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding robot that can navigate autonomously within the enclosure needs to be developed. To achieve the welding ra나, the robotic welding systems needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with work environmental map. At the same time a strategy for environment recognition for welding mobile robot is proposed in order to recognize the work environment efficiently. The design of the sensor system, the algorithm for sensing the structured environment, and the recognition strategy and tactics for sensing the work environment are described and dis-cussed in detail.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.5
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• pp.799-810
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• 2022

Welding work is a production work method widely used throughout the industry, and various types of welding technologies exist. In addition, many methods are being studied to automate these welding operations using robots, but in the ship manufacturing field, welding such as painting, cutting, and grinding is also the most common operation, but the manual operation ratio is higher than in other industries. Such a high manual labor ratio in the field of ship manufacturing not only causes quality problems and production delays according to the skill of workers, but also causes problems in the supply and demand of manpower. Therefore, this paper analyzed the reason why the automation rate is low in welding work at ship manufacturing sites compared to other industries, and analyzed the production process and field environment for small and medium-sized ship manufacturing companies that repeatedly manufactured with a small quantity production method. Based on the analysis results, it is intended to propose a robot system that can easily move between workplaces and secure uniform welding quality and productivity by collaborating simple welding tasks with humans. Finally, the simulation environment is constructed and analyzed to secure the suitability of robot system application to current production site environment, work process, and productivity, rather than to develop and apply the proposed robot system. Through such pre-simulation and robot system suitability analysis, it is expected to reduce trial and error that may occur in actual field installation and operation, and to improve the possibility of robot application and positive perception of robot system at ship manufacturing sites.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.776-787
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• 2002

Automation of welding process in shipyards is ultimately necessary, since the welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding mobile robot that can navigate autonomously within the enclosure has been developed. To achieve the welding task in the closed space, the robotic welding system needs a sensor system for the working environment recognition and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with 3D work environmental map. Using this sensor system, a spatial filter based on neural network technology is designed for extracting the center of laser stripe, and evaluated in various situations. An environment modeling algorithm structure is proposed and tested, which is composed of the laser scanning module for 3D voxel modeling and the plane reconstruction module for mobile robot localization. Finally, an environmental recognition strategy for welding mobile robot is developed in order to recognize the work environments efficiently. The design of the sensor system, the algorithm for sensing the partially structured environment with plane segments, and the recognition strategy and tactics for sensing the work environment are described and discussed with a series of experiments in detail.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.54.2-54
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• 2002

Robots are widely used for welding automation in the shipbuilding industry. Because of the distinguishing mark of the shipbuilding, many robots conduct each other welding jobs at a point of time. The manager/operator stay in a place apart from working site for safety reason, but need to observe the progress of work and the status of robots. On this account, the monitoring system for welding robots has become essential. We developed a monitoring system by which, many people can monitor robot's status simultaneously at separated locations through the web. The monitoring system consists of Server and Client, where the server keep connection to robots and deliver client's request to robots and cli...

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1116-1120
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• 2004

In the nuclear power plant, there are several cylindrical vessels such as reactor vessel, pressuriser and so on. The vessels are usually constructed by welding large rolled plates, forged sections or nozzle pipes together. In order to assure the integrity of the vessel, these welds should be periodically inspected using sensors such as ultrasonic transducer or visual cameras. This inspection is usually conducted under water to minimize exposure to the radioactively contaminated vessel walls. The inspections have been performed by using a conventional inspection machine with a big structural sturdy column, however, it is so huge and heavy that maintenance and handling of the machine are extremely difficult. It requires much effort to transport the system to the site and also requires continuous use of the utility's polar crane to move the manipulator into the building and then onto the vessel. Setup beside the vessel requires a large volume of work preparation area and several shifts to complete. In order to resolve these problems, we have developed an underwater mobile robot guided by the laser pointer, and performed a series of experiments both in the mockup and in the real reactor vessel. This paper introduces our robotic inspection system and the laser guidance of the mobile robot as well as the results of the functional test.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.16-22
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• 2019

Off-line programming and robot calibration through simulation are essential when setting up a robot in a robot automation production line. In this study, we developed a new robot calibration method to match the CAD data of the production line with the measurement data on the site using 3D scanner. The proposed method calibrates the robot using 3D point cloud data through Iterative Closest Point algorithm. Registration is performed in three steps. First, vertices connected by three planes are extracted from CAD data as feature points for registration. Three planes are reconstructed from the scan point data located around the extracted feature points to generate corresponding feature points. Finally, the transformation matrix is calculated by minimizing the distance between the feature points extracted through the ICP algorithm. As a result of applying the software to the automobile welding robot installation, the proposed method can calibrate the required accuracy to within 1.5mm and effectively shorten the set-up time, which took 5 hours per robot unit, to within 40 minutes. By using the developed system, it is possible to shorten the OLP working time of the car body assembly line, shorten the precision teaching time of the robot, improve the quality of the produced product and minimize the defect rate.