• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.226-232
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• 2015

As the age of smart device has come, recently many application services related to smart phone are developing. The LBS(Location Based Service) technique is considered as one of the most important techniques to support location based application services. Usually the smart phone acquires the information of position by using the position recognition systems and sensors such as GPS(Global Positioning System) and G-Sensor. However, since the GPS signal from the satellite can hardly be received in the indoor environments, new LBS techniques for the indoor environment are required. In this paper, to solve the problem a position information transceiver using LED lights and smart phone camera sensor is proposed. We proved the possibility of the proposed positioning system through the experiments in the laboratory for the practical verification.

• Journal of Aerospace System Engineering
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• v.15 no.1
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• pp.102-110
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• 2021

Recently, multi-copters equipped with various collision avoidance sensors have been introduced to improve flight stability. LiDAR is used to recognize a three-dimensional position. Multiple cameras and real-time SLAM technology are also used to calculate the relative position to obstacles. A three-dimensional depth sensor with a small process and camera is also used. In this study, a small collision-avoidance multi-copter system capable of in-door flight was developed as a platform for the development of collision avoidance software technology. The multi-copter system was equipped with LiDAR, 3D depth sensor, and small image processing board. Object recognition and collision avoidance functions based on the YOLO algorithm were verified through flight tests. This paper deals with recent trends in drone collision avoidance technology, system design/manufacturing process, and flight test results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.535-540
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• 2014

Due to the recent popularity of sports, business items which combine IT technologies with sports have appeared. 'Sportainment' which combines the elements of sports and entertainment have a lot of potential and development as new business items in the view of overcoming many limitations such as time and place in real sports. For suggesting a baseball simulation game 'sportainment', this paper is to review the technologies in the existing indoor baseball ranges and to provide the possibility of indoor baseball simulation using various sensor technologies. This baseball simulation game is expected to develop as one of successful indoor 'sportainment' businesses such as Golfzon.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.952-959
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• 2016

This paper proposes a novel indoor positioning system (IPS) that uses a calibrated camera sensor network and dense 3D map information. The proposed IPS information is obtained by generating a bird's-eye image from multiple camera images; thus, our proposed IPS can provide accurate position information when objects (e.g., the mobile robot or pedestrians) are detected from multiple camera views. We evaluate the proposed IPS in a real environment with moving objects in a wireless camera sensor network. The results demonstrate that the proposed IPS can provide accurate position information for moving objects. This can improve the localization performance for mobile robot operation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.437-438
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• 2019

본 논문에서는 ROS(Robot Operating System)기반으로한 로봇(Robot)에 레이저 거리 센서(LiDAR)를 설치하여 SLAM(Simultaneous Localization and Mapping : 동시적 위치 추적 지도 작성)기법으로 맵 정보를 습득하고, 저장하여 이를 기반으로 장애물과 건물의 실내 복도 안전하고 정확하게 순찰 할 수 있도록 하였다. 또한, 순찰 로봇(Robot)에 장착된 Raspberry카메라와 OpenCV 영상인식 기술을 이용하여 실시간 영상으로 실내 복도를 순찰하면서 사전에 설정된 특이사항이 있을 시 발견하고 기록하도록 시스템을 개발하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.848-849
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• 2023

본 논문은 로봇의 실내 환경에서의 자율성을 높이기 위한 SLAM과 내비게이션 방법을 제시한다. 2D LiDAR와 카메라를 이용하여 위치를 인식하고 사람과 장애물을 의미론적으로 검출하며, ICP와 RTAB-map, YOLOv3를 통합하여 Semantic Map을 생성하고 실내 환경에서 자율성을 유지한다. 이 연구를 통해 로봇이 복잡한 환경에서도 높은 수준의 자율성을 유지할 수 있는지 확인하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.111-112
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• 2023

학교, 대형 쇼핑몰, 공항 등과 같은 큰 실내 공간에서는 군중의 동선과 밀도를 파악하고 관리하는 것은 안전사고와 연관되어 있어 매우 중요하다. 와이파이 센싱은 기존에 존재하던 CCTV 카메라나 센서를 활용한 혼잡도 관리보다 효율적이고 정확한 방식으로 추정하는 데 도움이 되며, 설치 및 유지보수 측면에서도 효율적이다. 본 논문에서는 실내 환경에서 군중 수를 추정하기 위해 딥 러닝을 이용한 무선랜 신호 분석 기법을 제안한다. 송수신기가 같은 공간에 위치했던 기존 연구들과는 달리 본 논문에서는 송신기와 수신기가 서로 다른 공간에 배치된 환경에서도 무선랜 수신 신호를 통해 다른 공간의 군중 수를 정확히 예측할 수 있다는 것을 실험으로 검증하였다.

• Tunnel and Underground Space
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• v.20 no.3
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• pp.207-216
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• 2010

Rockfall monitoring systems generally used in the country are mainly based on the detection of tension of protection wire or tilting of protection post due to rock fall. However, rock fall protection net must be installed prior to the monitoring system and continual maintenance work after each rock fall event is required for a normal operation of these detection systems. To solve these problems, we suggested and implemented a non-contact rock fall detection system using multiple photo sensors and additional camera. After a laboratory experiment and field application, we can conclude that this system is effective and reliable for detecting, collecting and analyzing the rock fall information. In addition, lighten and difference operations on two captured images were able to yield rough estimation of size and direction of rock fall.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.65-72
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• 2011

In this paper, a real-time monocular vision based navigation system is developed for the disabled people, where online background learning and vector field histogram are used for identifying obstacles and recognizing avoidable paths. The proposed system is performed by three steps: obstacle classification, occupancy grid map generation and VFH-based path recommendation. Firstly, the obstacles are discriminated from images by subtracting with background model which is learned in real time. Thereafter, based on the classification results, an occupancy map sized at $32{\times}24$ is produced, each cell of which represents its own risk by 10 gray levels. Finally, the polar histogram is drawn from the occupancy map, then the sectors corresponding to the valley are chosen as safe paths. To assess the effectiveness of the proposed system, it was tested with a variety of obstacles at indoors and outdoors, then it showed the a'ccuracy of 88%. Moreover, it showed the superior performance when comparing with sensor based navigation systems, which proved the feasibility of the proposed system in using assistive devices of disabled people.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.111-120
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• 2022

It is essential to make a purchase decision to make sure that the furniture matches well with other structures in the room. Moreover, in the Untact Marketing situation caused by the COVID-19 crisis, this is becoming an even more impact factor. Accordingly, methods of measuring length using AR(Augmented Reality) are emerging with the advent of AR open sources such as ARCore and ARKit for furniture arrangement interior simulation. Since this existing method using AR generates a Depth Map based on a flat camera image and it also involves complex three-dimensional calculations, limitations are revealed in work that requires the information of accurate room size using a smartphone. In this paper, we propose a method to accurately measure the size of a room using only the accelerometer and gyroscope sensors built in smartphones without using ARCore or ARKit. In addition, as an example of application using the presented technique, a method for applying a pre-designed room interior to each room is presented.