• Proceedings of the KAIS Fall Conference
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• 2012.05b
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• pp.520-523
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• 2012

본 연구에서 무인차량의 자율주행시스템은 차량제어시스템, 항법시스템, 장애물인식시스템, 통합시스템의 4개 서브시스템으로 구성 되어있고, GPS와 레이저스캐너를 이용한 무인차량의 장애물인식시스템을 개발하고자 한다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.49-55
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• 2022

In this paper, we propose an obstacle detection method that can operate robustly even in external environmental factors such as weather. In particular, we propose an obstacle detection system that can accurately inform dangerous situations in AR through DB-based feature matching and RANSAC-based multiplane method. Since the approach to detecting obstacles based on images obtained by RGB cameras relies on images, the feature detection according to lighting is inaccurate, and it becomes difficult to detect obstacles because they are affected by lighting, natural light, or weather. In addition, it causes a large error in detecting obstacles on a number of planes generated due to complex terrain. To alleviate this problem, this paper efficiently and accurately detects obstacles regardless of lighting through DB-based feature matching. In addition, a criterion for classifying feature points is newly calculated by normalizing multiple planes to a single plane through RANSAC. As a result, the proposed method can efficiently detect obstacles regardless of lighting, natural light, and weather, and it is expected that it can be used to secure user safety because it can reliably detect surfaces in high and low or other terrains. In the proposed method, most of the experimental results on mobile devices reliably recognized indoor/outdoor obstacles.

• Journal of Aerospace System Engineering
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• v.14 no.2
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• pp.1-11
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• 2020

Detecting obstacles and generating a suitable path to avoid obstacles in real time is a prime mission requirement for UAVs. In areas, close to buildings and people, detecting obstacles in the path and estimating its own position (egomotion) in GPS degraded/denied environments are usually addressed with vision-based Simultaneous Localization and Mapping (SLAM) techniques. This presents possibilities and challenges for the feasible path generation with constraints of vehicle dynamics in the configuration space. In this paper, a near real-time feasible path is shown to be generated in the ORB-SLAM framework using a chain-based path planning approach in a force field with dynamic constraints on path length and minimum turn radius. The chain-based path plan approach generates a set of nodes which moves in a force field that permits modifications of path rapidly in real time as the reward function changes. This is different from the usual approach of generating potentials in the entire search space around UAV, instead a set of connected waypoints in a simulated chain. The popular ORB-SLAM, suited for real time approach is used for building the map of the environment and UAV position and the UAV path is then generated continuously in the shortest time to navigate to the goal position. The principal contribution are (a) Chain-based path planning approach with built in obstacle avoidance in conjunction with ORB-SLAM for the first time, (b) Generation of path with minimum overheads and (c) Implementation in near real time.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.567-569
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• 2006

This study proposes the method to make a map of moving environment area and passed area by sensor using for recognizing environment or avoiding obstacle. We win develop an efficient algorithm to use sensors and get the data by the user friendly system. Through this system, we win study the way to know of the driving environment of moving robot on the long distance point. To this, we use only one ultra-sonic sensor with a servo motor which rotates 180 degree and loads an ultra-sonic sensor. A sensor can measure 1m${\sim}$8m range and a servo motor can distinguish 15 degree by 12 divide of 180 degree. By this feature of operating system, the robot which has these sensor module detects around of area and moves another point. In this way, users gather the data of detecting distance and change the data to X-Y coordinates. And users derive a map from these accumulate data.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.418-420
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• 2005

This paper proposed ultrasonic distance measurement module development for correct distance detection with collision escaping or obstacle of mobile robot is traveling self-regulation. Representative ultrasonic module applied in existing was Polaroid company's 6500 series and Devantech company's SRF04/SRF08 series. This ultrasonic sensors are corrupted by systematic errors due mainly to the dependency of sound speed upon surrounding conditions and random errors of uncertain origin. Therefore Ultrasonic distance detecting means of error compensation method and high definition, narrow beam angle, board area distance detecting means to apply to ultrasonic mobile robot control urgently need. In this paper use internal type temperature compensation method to improve problem of ultrasonic distance measurement method instead of that volume that have shortcoming of used correct temperature compensation methods applied big addition device. Compensate error by environment change of temperature. Humidity density etc. and is applicable to mobile robot offering various interface and real-time processing developed possible distance measurement module.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1157-1162
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• 2013

This thesis describes the active cruise control which is a part of AVHS(Advanced Vehicle and Highway System) in the ITS(Intelligent Transportation Systems). The active cruise control is a system which recognizes some obstructions and vehicles in front, drives in safe speed and puts on the brake in dangerous situations as the driver simply turns on the switch without stepping on the accelerator and brake. PID controller is used in the speed-control by linearizing the longitudinal model of the vehicle, obstacle detecting algorithm which makes use of the laser scanner is proposed to recognize the situation in front and the system's performance is tested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.290-291
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• 2018

This paper suggests a design for an embedded system to control automobiles using mobile phones and applies the design on Arduino automobile models. Simulation of accidents that can happen in real life were conducted using Arduino automobile with attached sensors. The design includes algorithms for an automatic control that responds to events by detecting potential obstacles that maybe appear in the vehicle's surrounding and by measuring the distances between the obstacle and the vehicle. The feasibility of the suggested system is also reviewed.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1003-1013
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• 2016

This paper proposes a framework of superpixel-based vehicle detection method using plane normal vector in disparity space. We utilize two common factors for detecting vehicles: Hypothesis Generation (HG) and Hypothesis Verification (HV). At the stage of HG, we set the regions of interest (ROI) by estimating the lane, and track them to reduce computational cost of the overall processes. The image is then divided into compact superpixels, each of which is viewed as a plane composed of the normal vector in disparity space. After that, the representative normal vector is computed at a superpixel-level, which alleviates the well-known problems of conventional color-based and depth-based approaches. Based on the assumption that the central-bottom of the input image is always on the navigable region, the road and obstacle candidates are simultaneously extracted by the plane normal vectors obtained from K-means algorithm. At the stage of HV, the separated obstacle candidates are verified by employing HOG and SVM as for a feature and classifying function, respectively. To achieve this, we trained SVM classifier by HOG features of KITTI training dataset. The experimental results demonstrate that the proposed vehicle detection system outperforms the conventional HOG-based methods qualitatively and quantitatively.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2664-2666
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• 2005

In this paper, we develop the on board type image processing system using the CMOS sensor and the RISC type main processor. The main processor transmits YUV 4:2:2 type raw data captured by a CMOS image sensor to another processor(such as motion controller, PC, etc) via serial communication (rs232, SPI, I2C, etc). The role of another processor is line and obstacle detecting in image data received from the image processing board developed in this paper.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.78-86
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• 2017

The Internet of Things can offer disabled people the assistance and support, which is essential to achieve a good quality of life. The visually impaired people need assistance in finding locations, detecting obstacles on the way, and getting directions while moving around to reach their destination. Based on this persistent need, this paper proposes a navigation system for blind people using Internet of Things. The technologies used in our proposed system are: a smart cane containing an RFID reader and an ultrasonic sensor, a smart phone and Internet. The sensed data from the ultrasonic sensor for detecting obstacle is converted to International Standard format from ISO/IEC 23005-5 (MPEG-V Part 5). The system detects the blind person's location using the RFID tags implemented on the way. The system uses voice message in the smart phone to communicate with the blind person to lead him to his destination. The proposed system has been tested to navigate successfully in the campus.