• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.4
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• pp.19-25
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• 2008

This paper proposes a hierarchically structured navigation algorithm for autonomous mobile robot under unknown environment based on fuzzy-neal network. The proposed algorithm consists of two basic layers as follows. The lower layer consists of two parts such as fuzzy algorithm for goal approach and fuzzy-neural algorithm for obstacle avoidance. The upper layer which is basically fuzzy algorithm adjusts the magnitude of the weighting factor depending on the environmental situation. The proposed algorithm provides an efficient method to escape local mimimum points as shown in the simulation result. Most simulation results show that this algorithm is very effective for autonomous mobile robots' traveling in unknown field.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1372-1375
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• 2021

최근 산업 현장에서 많은 안전사고가 일어나고 있고, 현장 노동력의 부족으로 무인 로봇 시스템들을 도입하는 등 다양한 변화를 맞이하고 있다. 이에 차세대 자동화 시스템은 보다 유연하고 지능적이어야 한다. AGV(Automatic Guided Vehicle)의 경우 실시간으로 변하는 현장에 대응하기 어렵고, 새로운 어플리케이션에 대한 제품개발의 어려움이 따른다. 이에 대한 대안으로 AGV 인식 스택을 재구축하여 인간과 동일한 공간인식 능력을 갖춘 AMR(Autonomous Mobile Robot)이 대두되고 있다. 본 연구에서는 SLAM과 ROS를 이용하여 AMR의 기능을 구축하였다. YD Lidar 센서와 SLAM을 이용하여 주변 환경을 지도화 하여 로봇의 현재 위치를 파악할 수 있도록 제작하였고, 직접 지도상의 최적 경로를 파악하여 주변 장애물을 회피하며 주행할 수 있음을 확인하였다. DC 모터의 응답 특성에 따라 주행 속도, 조향각 등을 제어할 수 있도록 구현하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2078-2082
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• 2007

Recently, according to traffic accident statistics, traffic accidents occurring at night are as frequent as those during daytime, but their death rate is 1.5 times higher than that of daytime traffic accidents. This problem originates that the insufficient range of vision security of a driver causes the inappropriate accident confrontation. Therefore, in this paper, a microcontroller-based digital control method for the superior performance in headlight system is presented for optimal control that can adapt complex transient state, steady state and various environments. Specially in vehicles# headlight, its fundamental purpose is to implement the artificial headlight system which automatically controls the lighting patterns most adaptive to driving, road and weather conditions. Therefore we aimed at the development of headlight system, focused on the implementation of an artificial vehicle, of more advanced convenience and safety for drivers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.431-437
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• 2017

In this study, based on the RPS algorithm, the application results to an electrically controlled suspension system using previewed road information are presented. Reducing the excessive vibration induced by a disturbance transmitted to the system and secure its stability is a major issue. In particular, in the automotive industry, the demand is constantly being raised. A typical external disturbance causing vibration and instability of a vehicle is an irregular roadway surface that contacts a running vehicle tire. Therefore, obtaining such profile information is an important process. The RPS algorithm using a multi sensor system was constructed and implemented in a real car. Through experimental work using the RPS system included non-contact type optical sensors, it could robustly reconstruct the road input profiles from the intermixed data onto the vehicle's dynamic motion while traveling at an uneven roadway surface. A controller with a preview control was designed in the framework of a semi-active suspension system based on the 7 degrees of freedom full vehicle model. The control performance of the system was evaluated through simulations and the results were compared with the passive vehicle condition. These results highlight the feasibility of the presented control frame.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.151-160
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• 2010

For the realization of future intelligent transportation systems, fine-grained lane-by-lane traffic monitoring and control functionalities are among the most important technology barriers to overcome. To satisfy the accuracy requirement for traffic monitoring, a GNSS receiver network is designed. The designed receiver network consists of three different types of entities; reference server, broadcaster, and client. For deployment flexibility, all the entities utilize the international message standard RTCM SC-104 version 3.0. For fine-grained traffic monitoring, the client is designed to utilize position-domain carrier-smoothed-code filters to provide accurate vehicle coordinates in spite of frequent addages and outages of visible satellites. An experiment result is presented to evaluate the positioning accuracy of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.341-347
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• 2013

This study presents the remote control of a board robot using a Sensing glove based on Bluetooth communication. The board robot is a kind of riding robot controlled by an user. The user wears the proposed remote glove controller, and changes a direction of the robot by different kinds of finger actions. Bluetooth is used for wireless communication between the board robot and its user. CdS cell Sensors and a LED in the glove are used for recognition of a number of finger actions, which are measured as analog signals. The finger actions have five commands ('1'right '2'neutrality '3'left '4'operation '5'stop), which are transmitted from the user to the board robot through Bluetooth communication. Experimental results show that proposed a Sensing glove can effectively control the board robot.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.446-449
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• 2004

In the former researches〔2〕〔5〕 for the unmanned bicycle system, we do only focus on stabilizing it by using the lateral motion of mass which plays important role in driving a bicycle system. In this papers, we suggest an algorithm for deriving steering angle and speed for a given desired tracking path. As you may see in this paper, load mass balance system plays important role in stabilization and it is also discussed. We propose a control algorithm for the autonomous self stabilization of unmanned bicycle by using nonlinear compensation-like control based on the Lyapunov stability theory We then propose a tracking control strategy by moving the center of load mass left and right respectively. From the computer simulation results, we can show the effectiveness of the proposed control strategy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.237-240
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• 2005

본 본문은 Chus's 방정식과 Lorenz 방정식을 이용한 카오스 회로를 이동 로봇에 내장하여 카오스 이동 로봇을 구성하고 이 카오스 이동 로봇이 어느 임의 평면을 카오스 궤적을 가지고 주행 또는 탐색하다가 상호 연동 제어 명령이 내려지면 2개 또는 여러 개의 로봇이 서로 연동되어 동기화 되는 방법을 제시하고 그 결과를 검증하였다. 카오스 로봇 동기화에서는 장애물이 있는 경우와 은닉 장애물이 있는 경우에서 2개의 로봇이 서로 연동되어 움직이는지를 확인하였으며 만족할 만한 결과를 얻었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.81-86
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• 2020

With the development of the intelligent Internet of Things AIoT that goes beyond the IoT of the Internet of Things, the industry is changing overall. In addition, with the advent of the 4th Industrial Revolution, revolutionary changes and developments are also taking place in the automobile industry. A representative example is "autonomous driving vehicle". Because the domestic and foreign interests in autonomous vehicles have increased, many developments have been made, and although limited, they have developed into the commercialization stage. However, the structure of the autonomous vehicle that collects, analyzes, and controls data using various sensors installed in the vehicle, not the driver, is often insufficiently exposed to hacking due to the lack of multiplexed devices for security. In this case, as this can be a threat not only to the driver, but also to the surrounding environment, this paper proposes a new data processing function to improve the system security of autonomous vehicles.