• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.1144-1148
• /
• 1991

The problems occurred when developing a automatic wheel deburring system are to make effective flexibility in model change and the irregularity of the position/shape of the burr, to select optimal robotic manufacturing process and to develope optimal end effector. The locations where burr exists are on flange, rim and spoke. Here will be discussed the optimal solution for the removal of rim burr by using robot. The research can be summarized as the automatic robot path generation by recognizing rim contour and automatic deburring process technique. Various rim contour data is generated automatically when the sensor which is fixed to robot is moving with the parallel motion to the wheel center axis and this generated data is transferred to the data storage system and converted to the robot path data. The robotic tool system which is suitable to the rim deburring process is developed by integrating tool, compliance function and sensor. And factory automation system controlled by robot controller and PC is developed. This system shows good productivity and flexibility.

• Journal of Korea Multimedia Society
• /
• v.17 no.7
• /
• pp.787-796
• /
• 2014

Many mobile robot navigation methods utilize laser scanners, ultrasonic sensors, vision camera, and so on for detecting obstacles and path following. However, human utilizes only vision(e.g. eye) information for navigation. In this paper, we study a mobile robot control method based on only the camera vision. The Gaussian Mixture Model and a shadow removal technology are used to divide the foreground and the background from the camera image. The mobile robot uses a combined CAMSHIFT and KLT feature tracker algorithms based on the information of the foreground to follow a person. The algorithm is verified by experiments where a person is tracked and followed by a robot in a hallway.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.821-824
• /
• 1993

In hazardous conditions, where entry of human operators is restricted, such as high radiation regions in nuclear facilities, a lot of remote inspections and remote handling tasks must be performed. In this study, the stereo imaging system has been developed and the remote handling technique, has been studied to enhance the efficiency of tele-operation. The nozzle dam handling robot is one of the most important robots applied to nuclear facility. The robot will be equipped with the developed stereo imaging system. The stereo imaging system will outstandingly improve the tele installing/removal tasks for nozzle dam.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1769-1770
• /
• 2007

To prevent an insulator failure, an automatic cleaning robot was developed for suspension insulator strings. The robot autonomously moves along the insulator string using the clamps installed on its two moving frames, and adopts a dry cleaning method using rotating brushes and a circular motion guide. In addition, a mechanized brush bristles and a voltage-balancing contactor are devised to increase cleaning efficiency and to prevent arc generation under live-line conditions, respectively. Moreover, a manual tool for its installation and removal is presented. We confirmed its effectiveness through experiments.

• Journal of information and communication convergence engineering
• /
• v.19 no.1
• /
• pp.54-60
• /
• 2021

Various digital devices were supplied throughout the Fourth Industrial Revolution. Accordingly, the importance of data processing has increased. Data processing significantly affects equipment reliability. Thus, the importance of data processing has increased, and various studies have been conducted on this topic. This study proposes a modified Gaussian filter algorithm based on a fuzzy membership function. The proposed algorithm calculates the Gaussian filter weight considering the standard deviation of the filtering mask and computes an estimate according to the fuzzy membership function. The final output is calculated by adding or subtracting the Gaussian filter output and estimate. To evaluate the proposed algorithm, simulations were conducted using existing additive white Gaussian noise removal algorithms. The proposed algorithm was then analyzed by comparing the peak signal-to-noise ratio and differential image. The simulation results show that the proposed algorithm has superior noise reduction performance and improved performance compared to the existing method.

• Journal of information and communication convergence engineering
• /
• v.20 no.3
• /
• pp.195-203
• /
• 2022

Noise generated during image acquisition and transmission can negatively impact the results of image processing applications, and noise removal is typically a part of image preprocessing. Denoising techniques combined with nonlocal techniques have received significant attention in recent years, owing to the development of sophisticated hardware and image processing algorithms, much attention has been paid to; however, this approach is relatively poor for edge preservation of fine image details. To address this limitation, the current study combined a steering kernel technique with adaptive masks that can adjust the size according to the noise intensity of an image. The algorithm sets the steering weight based on a similarity comparison, allowing it to respond to edge components more effectively. The proposed algorithm was compared with existing denoising algorithms using quantitative evaluation and enlarged images. The proposed algorithm exhibited good general denoising performance and better performance in edge area processing than existing non-local techniques.

• The Journal of Korea Robotics Society
• /
• v.8 no.1
• /
• pp.51-57
• /
• 2013

Recently, the number of jellyfish has been rapidly grown because of the global warming, the increase of marine structures, pollution, and etc. The increased jellyfish is a threat to the marine ecosystem and induces a huge damage to fishery industries, seaside power plants, and beach industries. To overcome this problem, a manual jellyfish dissecting device and pump system for jellyfish removal have been developed by researchers. However, the systems need too many human operators and their benefit to cost is not so good. Thus, in this paper, the design, implementation, and experiments of autonomous jellyfish removal robot system, named JEROS, have been presented. The JEROS consists of an unmanned surface vehicle (USV), a device for jellyfish removal, an electrical control system, an autonomous navigation system, and a vision-based jellyfish detection system. The USV was designed as a twin hull-type ship, and a jellyfish removal device consists of a net for gathering jellyfish and a blades-equipped propeller for dissecting jellyfish. The autonomous navigation system starts by generating an efficient path for jellyfish removal when the location of jellyfish is received from a remote server or recognized by a vision system. The location of JEROS is estimated by IMU (Inertial Measurement Unit) and GPS, and jellyfish is eliminated while tracking the path. The performance of the vision-based jellyfish recognition, navigation, and jellyfish removal was demonstrated through field tests in the Masan and Jindong harbors in the southern coast of Korea.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.2
• /
• pp.214-219
• /
• 2007

In this paper, a new magnetic position sensing mettled for autonomous vehicle and robot guidance is presented. In autonomous vehicle and robot control, position sensing is an important task for the identification of their locations, such as the current position within a trajectory. The magnet based autonomous vehicle and robot was identified position via magnetic materials. In the magnetic sensing system, the Earth field is one of the largest disturbance. To removal of the Earth field, this paper proposes 1-dimensional magnetic field sensors array and develops precise petition sensing system using linear operating region of the magnetic field sensor. This proposal is verified a feasible magnetic position sensing system for autonomous vehicle and robot guidance by the experimental results.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.138.4-138
• /
• 2001

The purpose of this research is to build a quality-improved occupancy grid map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor environment. The AMR navigates in the unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. In order to increase the quality of the map we modify the Bayesian probability updating rule, reject non-systematic measurement errors and correct the predictable error of the AMR itself. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

• Proceedings of the IEEK Conference
• /
• 2002.06e
• /
• pp.153-156
• /
• 2002

The remotely operated underwater robotic vehicle system has been required to inspect some objects such as baffle former bolts and remove foreign objects in reactor vessel of nuclear power plant. In this paper, we have designed the remotely operated underwater robotic vehicle system that includes a long reach arm that is composed of 4 joints to remove foreign objects in a narrow space, a camera for visual test, instrument sensors for vehicle positioning, 4 thrusters for underwater navigation of vehicle, and supervisory control system implemented with industrial PC that includes robot simulator that has the functions of real time visualization, robot work planning and etc.