• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.610-615
• /
• 2005

Visual servoing is the fusion of results from many elemental areas including high-speed image processing, kinematics, dynamics, control theory, and real-time computing. It has much in common with research into active vision and structure from motion, but is quite different from the often described use of vision in hierarchical task-level robot control systems. We present a new approach to visual feedback control using image-based visual servoing with the stereo vision in this paper. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using a binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location but also at the other locations. The suggested technique can guide a robot manipulator to the desired location without giving such priori knowledge as the relative distance to the desired location or the model of an object even if the initial positioning error is large. This paper describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by the simulation and experimental results and compared with the case of conventional method for dual-arm robot made in Samsung Electronics Co., Ltd.

• Journal of Computational Design and Engineering
• /
• v.1 no.4
• /
• pp.243-255
• /
• 2014

The present study describes the development of control hardware and software for a mobile welding robot. This robot is able to move and perform welding tasks in a double hull structure. The control hardware consists of a main controller and a welding machine controller. Control software consists of four layers. Each layer consists of modules. Suitable combinations of modules enable the control software to perform the required tasks. Control software is developed using C programming under QNX operating system. For the modularizing architecture of control software, we designed control software with four layers: Task Manager, Task Planner, Actions for Task, and Task Executer. The embedded controller and control software was applied to the mobile welding robot for successful execution of the required tasks. For evaluate this imbedded controller and control software, the field tests are conducted, it is confirmed that the developed imbedded controller of mobile welding robot for shipyard is well designed and implemented.

• Journal of Welding and Joining
• /
• v.30 no.4
• /
• pp.44-48
• /
• 2012

H-beam used for stiffening the upper structure of ocean plant is cut in the various shapes. The cutting process of the H-beam is done manually and requires a long time and high cost. Therefore, automation of H-beam cutting is an important task. This research aims to develop a 3-D simulator to build the automatic H-beam cutting system and to determine the optimal cutting method. The automatic H-beam cutting system composes of 6 robots including 2 cutting robots hang to a crane and 1 conveyer. The appropriate system layout for covering the various sizes and types of H-beam was tested and determined using the simulator. The H-beam cutting system uses a hybrid type of plasma and gas cutting because of special cutting shapes of H-beam. The cutting area of each cutting method should be properly divided according to the size and shape of H-beam to shorten the total cutting time. Additionally the collision between a robot and a robot or a robot and H-beam should be avoided. The optimal cutting method for the shortest cutting time without the collision could be found for the various cutting conditions by use of the simulator. 2 simulation samples shows the availability of the simulator to find the optimal cutting method.

• Design & Manufacturing
• /
• v.18 no.2
• /
• pp.35-40
• /
• 2024

Injection molding is a process widely used across various industries for molding plastics, and it is the most commonly applied process in root industries utilizing molds. Among the different types of injection molding, insert injection molding, where busbars are used as inserts, is increasingly being applied in the electric vehicle industry. However, currently, the insert injection molding process is manually performed, with workers placing insert components by hand before injection molding. This results in issues related to productivity, safety, and quality. Additionally, there is a growing demand for automation of such production lines due to hazardous working conditions, economic difficulties in the manufacturing industry, and the decline in the labor force caused by an aging population. This study focuses on the application of an automated system for the insert injection molding process used in electric vehicles. The development of an automated system for the transport and insertion of insert components, as well as the inspection and stacking processes after injection, has resulted in over a 25% improvement in productivity and more than a 27% reduction in defect rates.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.04a
• /
• pp.381-386
• /
• 2002

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.6 no.4
• /
• pp.89-95
• /
• 1997

Welding technique is widely applied to general industry such as pressure vessel for chemical plant, pipe system, heavy industry, and automobile. There are some points which must be considered when robot system is used in welding automation process for productivity improvement. Welding quality is governed by heat input, and this quantity can be different according to shape, property, and thick of material . For desired heat input , weld input parameters such as welding voltage, current, and welding velocity must be determined with those consideration. Until now these parameters have been determined mainly by experience of operator. In this study, the size of welding zone was predicted by fuzzy rules were constructed from the relation between welding variables and weld pool size. Inverse model method which welding control input for welder is determined with optimum voltage and current by fuzzy controller is validatied by computer simulation.

• Journal of Mechanical Science and Technology
• /
• v.16 no.6
• /
• pp.762-769
• /
• 2002

This paper presents how effective it is to use many features for improving the speed and accuracy of visual servo systems. Some rank conditions which relate the image Jacobian to the control performance are derived. The focus is to describe that the accuracy of the camera position control in the world coordinate system is increased by utilizing redundant features in this paper. It is also proven that the accuracy is improved by increasing the number of features involved. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm robot manipulator made by Samsung Electronic Co. Ltd..

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2001.04a
• /
• pp.217-222
• /
• 2001

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

• Design & Manufacturing
• /
• v.16 no.4
• /
• pp.60-66
• /
• 2022

Recently, with the development of industry and the improvement of living standards, various wastes are generated along with the production of various products. Most of these wastes are used as containers for products, and plastic or aluminum is used. Various attempts are being made to automate the classification of these wastes due to the high labor cost, but most of them are solved by manpower due to the geometrical shape change due to the nature of the waste. In this study, in order to automate the waste sorting task, Deep Learning technology is applied to a robot system for waste sorting and a vision system for waste sorting to effectively perform sorting tasks according to the shape of waste. As a result of the experiment, a Deep Learning parameter suitable for waste sorting was selected. In addition, through various experiments, it was confirmed that 99% of wastes could be selected in individual & group image learning. It is expected that this will enable automation of the waste sorting operation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.276-279
• /
• 2009

Is introducing ship automation system for the safety of ship and work environment mend recently. Is endeavoring for sea safety and fire at sea prevention solidifying control of standard technology and safety supervision aspect in IMO but sea accident and ship fire are happening continuously. Because using Robot in artistic talent of ship in this treatise, studied that correspond to Risk and manage. Attach fire perception sensor for Robot's Risk confrontation, and because using infrared rays sensor, TOUCH SWITCH, sound perception sensor, gas perception sensor, light perception sensor that is threaded in Robot and is achieved, controlled Robot, and establish Low-High value the speed of sound output use and DC MOTOR and COM SEN of when indicate Risk confrontation to Robot and establish Robot's Risk confrontation administration action.