• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.24-33
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• 1996

PLCs are vital components of modern automation systems, which have penetrated into almost every industry. Many industries have a demand for facilitation of PLC programming. In this study, a programning system for sequential control is developed on a personal computer. This programming system consists of two main parts, a GRAFCET editor and a GRAFCET compiler. The GRAFCET editor enables us to model an actual sequential process by a GRAFCET diagram. This GRAFCET editor is developed by the menu-driven method based on specific menus and graphic symbols. The GRAFCET compiler consists of two parts, a GRAFCET parser and a code generator. The possible errors in a drawn GRAFCET diagram are first checked by the GRAFCET parser which generates finally an intermediate code from a verified CRAFCET diagram. Then the intermediate code is converted into a control code of an actual sequential controller by the code generator. To show the usefulness of this programming system, this system is applied to a pneumatically controlled handling robot. For this robot, a Z-80 microprocessor is used as the actual sequential controller.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.265-276
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• 2024

The future battlefield operation concept does not focus on advanced and complete weapon systems, but requires a new battlefield operation concept that can effectively demonstrate offensive power by combining a large number of low-cost, miniaturized weapons. Recently, research on the autonomous application of major technologies that make up the mission control system is actively underway. However, since the mission control system is still dependent on the operator's operating ability when operating multiple robots, there are limitations to simply applying the automation technology of the existing mission control system. Therefore, we understand how changes in operator capabilities affect multi-robot operation and propose an adaptive mission control architecture design method that supports multi-robot integrated operation by adjusting the level of autonomy of the mission control system according to changes in operator capability.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.10
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• pp.1025-1031
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• 2007

GPS is widely used for positioning applications and attitude of a vehicle can be found also with multiple antennas. However, extremely weak signal level prevents GPS from indoor operation. DR with accelerometers and gyros and landmark based localization method used for indoor applications increase complexity and cost. In this paper, a simple but very efficient ultrasound based attitude determination system which determines both position and attitude in WSN is given. The range between transmitter and receivers are measured using the arrival time difference between ultrasound and RF signal. The 3 dimensional positions can be found using more than 3 range measurements. Furthermore, if more than 2 transmitters are used, the attitude can be determined using the baseline vectors obtained by differencing transmitter and receiver positions. The prototype system is implemented to evaluate the performance of the proposed method. In addition, an error analysis shows the relation between the attitude error and basel me length, quality of measurement and orientation of a vehicle. The static and dynamic experiments performed by micro mobile robot shows accurate position with less than 1.5cm error and attitude with less than 1 degree error can be obtained continuously with 20cm baseline. It is expected that these results can be adapted without modification to indoor applications such as home cleaning robot and autonomous wheelchair maneuvering.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.349-355
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• 2015

Underwater robots generally show better performances for tasks than humans under certain underwater constraints such as. high pressure, limited light, etc. To properly diagnose in an underwater environment using remotely operated underwater vehicles, it is important to keep autonomously its own position and orientation in order to avoid additional control efforts. In this paper, we propose an efficient method to assist in the operation for the various disturbances of a remotely operated vehicle for the diagnosis of underwater structures. The conventional AHRS-based bearing estimation system did not work well due to incorrect measurements caused by the hard-iron effect when the robot is approaching a ferromagnetic structure. To overcome this drawback, we propose a sensor fusion algorithm with the camera and AHRS for estimating the pose of the ROV. However, the image information in the underwater environment is often unreliable and blurred by turbidity or suspended solids. Thus, we suggest an efficient method for fusing the vision sensor and the AHRS with a criterion which is the amount of blur in the image. To evaluate the amount of blur, we adopt two methods: one is the quantification of high frequency components using the power spectrum density analysis of 2D discrete Fourier transformed image, and the other is identifying the blur parameter based on cepstrum analysis. We evaluate the performance of the robustness of the visual odometry and blur estimation methods according to the change of light and distance. We verify that the blur estimation method based on cepstrum analysis shows a better performance through the experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1284-1289
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• 2014

In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.369-376
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• 2015

Chemicals are injected in order to remove a variety of organic substances contained in the water purification plant influent. It can be determined with measuring sedimentation turbidity 4~7 hours later, whether the chemical dosage rate is proper or not, which make the real-time feedback control impossible. In addition, manual operation in accordance with the Jar-Test carried out in the laboratory and the operator's experience may cause the experimental and human error by the changes of organic characteristics and water quality. Especially at night ad weekend, the rate have been determined only by the operator judgment owing to environment engineer's absence. Therefore, the decision of optimal chemical dosage rate using proposed intelligent control algorithm is expected to result in real-time injection and cost reduction.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.706-711
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• 2008

This paper is presented an accurate localization scheme for mobile robots based on the fusion of ultrasonic satellite (U-SAT) with inertial navigation system (INS), i.e., sensor fusion. Our aim is to achieve enough accuracy less than 100 mm. The INS consist of a yaw gyro, two wheel-encoders. And the U-SAT consist of four transmitters, a receiver. Besides the localization method in this paper fuse these in an extended Kalman filter. The performance of the localization is verified by simulation and two actual data(straight, curve) gathered from about 0.5 m/s of driving actual driving data. localization methods used are general sensor fusion and sensor fusion through Kalman filter using data from INS. Through the simulation and actual data studies, the experiment show the effectiveness of the proposed method for autonomous mobile robots.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.783-789
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• 2001

The purpose of this study is to build and to manage environment models with line segments from the sonar range data on obstacles in unknown and varied environments. The proposed method subsequently employs a two-stage data-transform process in order to extract environmental line segments from the range data on obstacles. In the first stage, the occupancy grid extracted from the range data is accumulated to a two-dimensional local histogram grid. In the second stage, a line histogram extracted from an local histogram gird is based on a Hough transform, and matching is a process of comparing each of the segments in the global line segments map against the line segments to detect similarity in overlap, orientation, and arrangement. Each of these tests is made by comparing one of the parameters in the segment representation. After the tests, new line segments are composed to the global line segments map. The proposed technique is illustrated by experiments in an indoor environment.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.749-757
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• 2001

We present a simple artificial landmark model and robust landmark tracking algorithm for mobile robot localization. The landmark model, consisting of symmetric and repetitive color patches, produces color histograms that are invariant under the geometric and photometric distortions. A stochastic approach based on the CONDENSATION tracks the landmark model robustly even under the varying illumination conditions. After the landmark detection, relative position of the mobile robot to the landmark is calculated. Experimental results show that the proposed landmark model is effective and can be detected and tracked in a clustered scene robustly. With the tracked single landmark, we extract geometrical information than achieve accurate localization.