• 제어로봇시스템학회논문지
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• 제17권6호
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• pp.521-525
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• 2011

Lane marking detection is one of important issues in the field of autonomous mobile robot. Especially, in urban environment, like pavement roads of downtown or tour tracks of Science Park, which have continuous patterns on the surface of the road, the lane marking detection becomes more important ability. Although there were many researches about lane detection and lane tracing, many of them used vision sensors mainly to detect lane marking. In this paper, we obtain 2 dimensional library data of 'Intensity' and 'Distance' using one laser rangefinder only. We design a simple classifier and filtering algorithm for the lane detection which uses only one LRF (Laser Range Finder). Allowing extended usage of LRF, this research provides more functionality not only in range finding but also in lane detecting to mobile robots. This work will be technically helpful for robot developers to design more simple and efficient autonomous driving system using LRF.

• 대한안전경영과학회지
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• 제25권3호
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• pp.17-22
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• 2023

As the importance of artificial intelligence grows rapidly and emerges as a leader in technology, it is becoming an important variable in the next-generation industrial system along with the robot industry. In this study, a safety system was developed using deep learning technology to provide worker safety in a robot workplace environment. The implemented safety system has multiple cameras installed with various viewing directions to avoid blind spots caused by interference. Workers in various scenario situations were detected, and appropriate robot response scenarios were implemented according to the worker's risk level through IO communication. For human detection, the YOLO algorithm, which is widely used in object detection, was used, and a separate robot class was added and learned to compensate for the problem of misrecognizing the robot as a human. The performance of the implemented system was evaluated by operator detection performance by applying various operator scenarios, and it was confirmed that the safety system operated stably.

• 로봇학회논문지
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• 제17권2호
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• pp.172-177
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• 2022

In general, detection robots using ultrasonic sensors are equipped with sensors to protrude outward or to contact objects. However, in the case of a screw-propelled robot that detects the inside of a reactor tendon duct, if the ultrasonic sensor protrudes to the outside, resistance due to grease is generated, and thus the propulsion efficiency is reduced. In order to increase the propulsion efficiency, the screw must be sharp, and the sharper the screw, the more difficult it is to apply a high-performance ultrasonic sensor, and the detection efficiency decreases. This paper proposes a screw shape-changing mechanism that can improve both propulsion efficiency and detection efficiency. This mechanism includes an overlapped helical ring (OHR) structure and a magnetic clutch system (MCS), and thus the shape of a screw may be changed to a compact size. As a result, the Screw-propelled robot with this mechanism can reduce the overall length by about 150 mm and change the shape of the screw faster and more accurately than a robot with a linear actuator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.300-302
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• 2006

Middleware offers function that user application program can transmit data independently of network device. Connection management about network connection of module is important for normal service of module base personal robot. Unpredictable network disconnection is influenced to whole robot performance in module base personal robot. For this, Middleware must be offer two important function. The first is function of error detection and reporting about abnormal network disconnection. Therefore, middleware need method for network error detection and module management to consider special quality that each network device has. The second is the function recovering that makes the regular service possible. When the module closed from connection reconnects, as this service reports connection state of the corresponding module, the personal robot resumes the existing service. In this paper proposed method of network connection management for to support fault tolerant about network error of network module based personal robot.

• 한국멀티미디어학회논문지
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• 제25권6호
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• pp.833-843
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• 2022

Based on the problems of untimely Expressway fire rescue and backward traditional fire rescue methods, an emergency fire fighting and inspection robot riding on expressway guardrail is designed. The overall mechanical structure design of emergency fire fighting and inspection robot riding on expressway guardrail is completed by using three-dimensional design software. The target fire detection is realized by using the target detection algorithm of Yolov5; By selecting a variety of sensors and using the control method of multi algorithm fusion, the basic function of robot on duty early warning is realized, and it has the ability of intelligent fire extinguishing. The BMS battery charging and discharging system is used to detect the real-time power of the robot. The design of the expressway emergency fire fighting and inspection robot provides a new technical means for the development of emergency fire fighting equipment, and improves the reliability and efficiency of expressway emergency fire fighting.

• 한국지능시스템학회논문지
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• 제24권4호
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• pp.437-442
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• 2014

최근에는 크기 및 비용의 관점에서 많은 장점을 갖는 초소형 해양로봇(Micro Marine Robot : MMR)의 개발 및 적용에 대한 요구가 증가하고 있다. 하지만 국내에서는 그 기반이 매우 부족한 상황이다. 다행히도 초소형 수상로봇(Micro Surface Robot : MSR)의 장애물회피와 관련해서는 크기와 성능의 관점에서 최적화되어 4방향 탐지가 가능한 장애물회피소나(Obstacle Avoidance Sonar : OAS)가 개발되었으나, 제한된 빔폭(beam width) 및 탐지거리를 갖는 고정 소나빔의 사용으로 인하여 장애물의 형상에 따라 탐지성능이 저하되는 문제점이 존재했다. 이러한 문제를 해결하기 위하여, 본 논문에서는 평기어(spur gear) 및 서보모터를 활용하여 회전 소나빔을 구현한 MSR의 메커니즘을 제안하였다. 제안된 메커니즘의 검증을 위해 다각 평면 장애물에 대한 MSR의 벽면 추적(wall-tracking) 문제를 고려하였고, 탐지성능 및 구동명령 측면에서 기존의 고정 소나빔 적용 시와 비교 및 분석을 수행하였다. 실험결과는 제안된 메커니즘의 타당성을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2337-2341
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• 2005

This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.

• 로봇학회논문지
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• 제10권4호
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• pp.223-229
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• 2015

This paper proposes a novel method for detection of hand raising poses from images acquired from a single camera attached to a mobile robot that navigates unknown dynamic environments. Due to unconstrained illumination, a high level of variance in human appearances and unpredictable backgrounds, detecting hand raising gestures from an image acquired from a camera attached to a mobile robot is very challenging. The proposed method first detects faces to determine the region of interest (ROI), and in this ROI, we detect hands by using a HOG-based hand detector. By using the color distribution of the face region, we evaluate each candidate in the detected hand region. To deal with cases of failure in face detection, we also use a HOG-based hand raising pose detector. Unlike other hand raising pose detector systems, we evaluate our algorithm with images acquired from the camera and images obtained from the Internet that contain unknown backgrounds and unconstrained illumination. The level of variance in hand raising poses in these images is very high. Our experiment results show that the proposed method robustly detects hand raising poses in complex backgrounds and unknown lighting conditions.

• 제어로봇시스템학회논문지
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• 제13권2호
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• pp.140-146
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• 2007

This paper demonstrates the development of a mobile robot for patrol. We fuse differential GPS, angle sensor and odometry data using the framework of extended Kalman filter to localize a mobile robot in outdoor environments. An important feature of road environment is the existence of curbs. So, we also propose an algorithm to find out the position of curbs from laser range finder data using Hough transform. The mobile robot builds the map of the curbs of roads and the map is used fur tracking and localization. The patrol robot system consists of a mobile robot and a control station. The mobile robot sends the image data from a camera to the control station. The remote control station receives and displays the image data. Also, the patrol robot system can be used in two modes, teleoperated or autonomous. In teleoperated mode, the teleoperator commands the mobile robot based on the image data. On the other hand, in autonomous mode, the mobile robot has to autonomously track the predefined waypoints. So, we have designed a path tracking controller to track the path. We have been able to confirm that the proposed algorithms show proper performances in outdoor environment through experiments in the road.

• 로봇학회논문지
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• 제6권4호
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• pp.334-343
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• 2011

This paper presents a new approach for mobile robot heading detection using MEMS Gyro north finding method in the indoor environment. Based on this, the robot heading angle measurement scheme is proposed; improved north finding theory and algorithm are also explained. Several approaches are applied to confirm system's precision and effectiveness. In order to find out the heading angle, a single axis MEMS gyroscope to sense the angle between the robot heading direction and the north is used. To reach enough estimation accuracy and reduce detection time, the least square method (LSM) for the signal fitting and parameter estimation is applied. Through a turn-table, we setup a carouseling system to decrease the substantial bias effect on gyroscope's heading angle. For the evaluation of the proposed method, this system is implemented to the Pioneer robot platform. The performance and heading error are analyzed after the test. From the simulation and experimental results, system's accuracy, usefulness and adaptability are shown.