• Proceedings of the KAIS Fall Conference
• /
• 2010.05b
• /
• pp.610-613
• /
• 2010

본 과제를 통하여 기술적으로는 로봇 개발에 있어 기존 기술을 최대한 활용하고 새로운 기능을 추가하는 형태로 발전해 갈 수 있도록, 각 요소별 기능을 표준화 모듈화 하여 새로운 제품의 개발이 손쉽게 이루어 질 수 있는 기본 platform으로의 역할이 가능해졌다. 구동부 제작 및 설계, 금형 비용 등을 절감하기 위한 다목적 완구로봇 플랫폼을 확보할 수 있었다. 로봇이 복잡한 환경을 인식하고, 자율적으로 작업을 수행하며, 예측하지 못한 문제에 적절한 대처를 할 수 있도록 하기 위한 핵심 기술을 제공하게 될 것으로 생각된다. 로봇 개발에 있어 전문지식이 없는 초보자들이 직접 제작 구동해 볼 수 있는 비주얼한 개발환경을 지원할 뿐만 아니라 GUI 개발환경 및 TEXT Programming 으로 상호 전환이 가능한 코딩 방법을 지원(MSRS와의 차별화를 시도하였다. 기존 하드웨어 지식과 소프트웨어지식이 없는 상태에서도 제작자의 창의력에 따라 다양한 형태의 로봇을 제작 적용이 용의 하며 초보자들에 대한 로봇개발에 흥미를 유발할 수 있도록 하였다. 고급사용자를 위한 별도의 다운로딩 포트를 제공하였다. 로봇공학의 기본지식을 습득(아날로그/디지털 회로를 이해하고, 각종 센서의 이해하며, 스템/서보/DC모터의 제어기술, 펌웨어개발능력, 기본수준의 소프트웨어개발 능력) 활용할 수 있다. 또한, 경제 및 산업적 측면으로는 다음과 같은 장점이 있다. 기존 기술들의 장점을 취합하여 추가적인 기술을 적용할 수 있는 Base형태의 로봇을 개발할 경우 이를 활용한 제품 개발 및 Base자체로도 충분한 시장을 형성 할 수 있을 것으로 기대된다. 인터넷기반 로봇 제어 기술의 확보로 로봇시스템의 생산비용을 낮추고 TTM (Time-to-Market) 제약을 해결시켜 준다. 다른 응용 시스템에 쉽게 적용이 가능하고 지식기반 로봇 서비스의 요소기술 개발은 멀티미디어 콘텐츠분야(교육/게임/오락 등)의 활성화가 가능하기 때문에 타 IT산업에의 파급효과가 예상된다. B2B를 통한 실질적인 판매를 통한 동종기업의 연구 개발비 및 개발 기간의 단축이 예상된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.731-733
• /
• 2016

The primary goal of the line tracer is to accurately and quickly detect the movement up to the target position given by the sensor juhaengseon. It has been used in applications in various fields such as the current unmanned transport vehicles, laser cutting machine, autonomous mobile robots and unmanned driving is possible, and is held annually at various universities in the competition field with the possibility of great progress, depending on the application. However, there arises a large difference in running performance, depending on the hardware design and control. In this paper, improving the characteristics of the tracer line and characters to design a PID controller is to apply the point on ways of improving the properties of the system.

• International journal of advanced smart convergence
• /
• v.7 no.1
• /
• pp.42-47
• /
• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.5
• /
• pp.364-371
• /
• 2016

We developed a prediction model of assistance force for the opening/closing of an automobile door depending on the condition of the parking ground. The candidates of the learning models for the operating assistance force were compared to determine the proper force according to the slope and user's force, etc. The reduced experimental model was developed to obtain learning data for the estimation model. The learning algorithm was composed to predict the assistance force to incorporate real assistance force data. Among these algorithms, an Artificial Neural Network (ANN) and Support Vector Machine(SVM) were applied and the adaptability was compared between these models. The SVM provided more adaptability for the learning process of the door assistance force prediction. This paper proposes a system for determining the assistance force to control a door motor to compensate for the deviation of required door force in the slope condition, as needed in the plane condition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.549-551
• /
• 2016

In this paper, With the development of modern science and technology are Sheds to stay indoors rather than outdoors space it increased significantly compared to the past. And a wide variety of research about outdoor air quality until recently, efforts are underway but the issue of air quality in the room is the fact that all considered relatively lightly. As the contamination of the room air is polluted, unlike the natural environment, a large outdoor air dilution rate, the dilution rate is very low, once the contaminated air continuously circulating exerts a very bad influence on the health of people staying in the room. In this study, movement characteristics of the person living in a room, the air measuring device for the study of the active indoor environmental control system reflects the life form to measure the quality of the measured air in real time for transmitting the information to the user of the smart devices, alarm bot It was implemented and operational applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.845-847
• /
• 2014

In recent years, the mobile OS market, enlargement and, at the same time, Android has mounted various smart phones and feature air conditioning, smart TV, cleaning robot, camera, etc. that the number is being spread at a rapid pace. But a lot of devices to control the modules and applications at once, this is not a device for controlling the dissemination of applications all in one place, and in charge of the devices that allow you to manage applications are lacking. Accordingly, in this paper, use the Web Server registered in the appliance can be controlled by management, Web access, is proposing and designing the system. This is the current research is actively in progress in the field of IoT (Internet of Things) would be utilized.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.10
• /
• pp.1310-1316
• /
• 2021

Recently, with the development of artificial intelligence and IoT technology, the importance of video processing such as object tracking, medical imaging, and object recognition is increasing. In particular, the noise reduction technology used in the preprocessing process demands the ability to effectively remove noise and maintain detailed features as the importance of system images increases. In this paper, we provide a modified weight filter based on pixel matching in an AWGN environment. The proposed algorithm uses a pixel matching method to maintain high-frequency components in which the pixel value of the image changes significantly, detects areas with highly relevant patterns in the peripheral area, and matches pixels required for output calculation. Classify the values. The final output is obtained by calculating the weight according to the similarity and spatial distance between the matching pixels with the center pixel in order to consider the edge component in the filtering process.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.2
• /
• pp.207-213
• /
• 2022

Recently, with the improvement of the performance of IoT technology and AI, automation and unmanned work are progressing in a wide range of fields, and interest in image processing, which is the basis of automation such as object recognition and object classification, is increasing. Image noise removal is an important process used as a preprocessing step in an image processing system, and various studies have been conducted. However, in most cases, it is difficult to preserve detailed information due to the smoothing effect in high-frequency components such as edges. In this paper, we propose an algorithm to restore damaged images in AWGN(additive white Gaussian noise) using fuzzy weights based on Gaussian distribution. The proposed algorithm switched the filtering process by comparing the filtering mask and the noise estimate with each other, and reconstructed the image by calculating the fuzzy weights according to the low-frequency and high-frequency components of the image.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.12
• /
• pp.1846-1852
• /
• 2021

In modern society, various digital devices are being distributed in a wide range of fields due to the fourth industrial revolution and the development of IoT technology. However, noise is generated in the process of acquiring or transmitting an image, and not only damages the information, but also affects the system, causing errors and incorrect operation. AWGN is a representative noise among image noise. As a method for removing noise, prior research has been conducted, and among them, AF, A-TMF, and MF are the representative methods. Existing filters have a disadvantage that smoothing occurs in areas with high frequency components because it is difficult to consider the characteristics of images. Therefore, the proposed algorithm calculates the standard deviation distribution to effectively eliminate noise even in the high frequency domain, and then calculates the final output by applying the probability density function weight of the Laplace distribution using the curve fitting method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.975-976
• /
• 1993

This talk presents the overview of the author's research and development activities on fuzzy inference hardware. We involved it with two distinct approaches. The first approach is to use application specific integrated circuits (ASIC) technology. The fuzzy inference method is directly implemented in silicon. The second approach, which is in its preliminary stage, is to use more conventional microprocessor architecture. Here, we use a quantitative technique used by designer of reduced instruction set computer (RISC) to modify an architecture of a microprocessor. In the ASIC approach, we implemented the most widely used fuzzy inference mechanism directly on silicon. The mechanism is beaded on a max-min compositional rule of inference, and Mandami's method of fuzzy implication. The two VLSI fuzzy inference chips are designed, fabricated, and fully tested. Both used a full-custom CMOS technology. The second and more claborate chip was designed at the University of North Carolina(U C) in cooperation with MCNC. Both VLSI chips had muliple datapaths for rule digital fuzzy inference chips had multiple datapaths for rule evaluation, and they executed multiple fuzzy if-then rules in parallel. The AT & T chip is the first digital fuzzy inference chip in the world. It ran with a 20 MHz clock cycle and achieved an approximately 80.000 Fuzzy Logical inferences Per Second (FLIPS). It stored and executed 16 fuzzy if-then rules. Since it was designed as a proof of concept prototype chip, it had minimal amount of peripheral logic for system integration. UNC/MCNC chip consists of 688,131 transistors of which 476,160 are used for RAM memory. It ran with a 10 MHz clock cycle. The chip has a 3-staged pipeline and initiates a computation of new inference every 64 cycle. This chip achieved an approximately 160,000 FLIPS. The new architecture have the following important improvements from the AT & T chip: Programmable rule set memory (RAM). On-chip fuzzification operation by a table lookup method. On-chip defuzzification operation by a centroid method. Reconfigurable architecture for processing two rule formats. RAM/datapath redundancy for higher yield It can store and execute 51 if-then rule of the following format: IF A and B and C and D Then Do E, and Then Do F. With this format, the chip takes four inputs and produces two outputs. By software reconfiguration, it can store and execute 102 if-then rules of the following simpler format using the same datapath: IF A and B Then Do E. With this format the chip takes two inputs and produces one outputs. We have built two VME-bus board systems based on this chip for Oak Ridge National Laboratory (ORNL). The board is now installed in a robot at ORNL. Researchers uses this board for experiment in autonomous robot navigation. The Fuzzy Logic system board places the Fuzzy chip into a VMEbus environment. High level C language functions hide the operational details of the board from the applications programme . The programmer treats rule memories and fuzzification function memories as local structures passed as parameters to the C functions. ASIC fuzzy inference hardware is extremely fast, but they are limited in generality. Many aspects of the design are limited or fixed. We have proposed to designing a are limited or fixed. We have proposed to designing a fuzzy information processor as an application specific processor using a quantitative approach. The quantitative approach was developed by RISC designers. In effect, we are interested in evaluating the effectiveness of a specialized RISC processor for fuzzy information processing. As the first step, we measured the possible speed-up of a fuzzy inference program based on if-then rules by an introduction of specialized instructions, i.e., min and max instructions. The minimum and maximum operations are heavily used in fuzzy logic applications as fuzzy intersection and union. We performed measurements using a MIPS R3000 as a base micropro essor. The initial result is encouraging. We can achieve as high as a 2.5 increase in inference speed if the R3000 had min and max instructions. Also, they are useful for speeding up other fuzzy operations such as bounded product and bounded sum. The embedded processor's main task is to control some device or process. It usually runs a single or a embedded processer to create an embedded processor for fuzzy control is very effective. Table I shows the measured speed of the inference by a MIPS R3000 microprocessor, a fictitious MIPS R3000 microprocessor with min and max instructions, and a UNC/MCNC ASIC fuzzy inference chip. The software that used on microprocessors is a simulator of the ASIC chip. The first row is the computation time in seconds of 6000 inferences using 51 rules where each fuzzy set is represented by an array of 64 elements. The second row is the time required to perform a single inference. The last row is the fuzzy logical inferences per second (FLIPS) measured for ach device. There is a large gap in run time between the ASIC and software approaches even if we resort to a specialized fuzzy microprocessor. As for design time and cost, these two approaches represent two extremes. An ASIC approach is extremely expensive. It is, therefore, an important research topic to design a specialized computing architecture for fuzzy applications that falls between these two extremes both in run time and design time/cost. TABLEI INFERENCE TIME BY 51 RULES {{{{Time }}{{MIPS R3000 }}{{ASIC }}{{Regular }}{{With min/mix }}{{6000 inference 1 inference FLIPS }}{{125s 20.8ms 48 }}{{49s 8.2ms 122 }}{{0.0038s 6.4㎲ 156,250 }} }}