• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.79-82
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• 2005

Recently the necessity of road data is still being increased in industrial society, so there are many repairing and new constructions of roads at many areas. According to the development of government, city and region, the update and acquisition of road data for GIS (Geographical Information System) is very necessary. In this study, the fusion method with range data(3D Ground Coordinate System Data) and Intensity data in stand alone LiDAR data is used for road extraction and then digital image processing method is applicable. Up to date Intensity data of LiDAR is being studied. This study shows the possibility method for road extraction using Intensity data. Intensity and Range data are acquired at the same time. Therefore LiDAR does not have problems of multi-sensor data fusion method. Also the advantage of intensity data is already geocoded, same scale of real world and can make ortho-photo. Lastly, analysis of quantitative and quality is showed with extracted road image which compare with I: 1,000 digital map.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.177-180
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• 2008

Many researches have been tried to extract building models and created a 3D cyber city from LiDAR data. In this paper, the approach of extracting complex building by using airborne LiDAR data combined with airborne orthoimagery has been performed. The pseudo-building elevations were derived from modified discrete return LiDAR data. Based on information property of the pseudo-height, building features could be extracted. The results of this study indicated the improvement of building extraction.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 추계학술발표대회
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• pp.681-682
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• 2016

In this study we propose a novel approach to segment a terrain in two parts: ground and none-ground. The terrain is gained by a multi-channel 3D laser range sensor. We process each vertical line in each frame data. The vertical line is bounded by the sensor's position and a point in the largest circle of the frame. We consider each pair of two consecutive points in each line to find begin-ground and end-ground points. All points placed between a begin-ground point and an end-ground point are ground ones. The other points are none-ground. After examining all vertical lines in the frame, we obtain the terrain segmentation result.

• 대한임베디드공학회논문지
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• 제15권6호
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• pp.269-279
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• 2020

This paper presents the design and implementation of embedded systems and autonomous path generation for autonomous speed sprayer. Autonomous Orchard Systems can be divided into embedded controller and path generation module. Embedded controller receives analog sensor data, on/off switch data and control linear actuator, break, clutch and steering module. In path generation part, we get 3D cloud point using Velodyne VLP16 LIDAR sensor and process the point cloud to generate maps, do localization, generate driving path. Then, it finally generates velocity and rotation angle in real time, and sends the data to embedded controller. Embedded controller controls steering wheel based on the received data. The developed autonomous speed sprayer is verified in test-bed with apple tree-shaped artworks.

• 한국측량학회지
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• 제25권6_1호
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• pp.545-555
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• 2007

3D buildings are the most prominent feature comprising urban scene. A few of mega-cities in the globe are virtually reconstructed in photo-realistic 3D models, which becomes accessible by the public through the state-of-the-art online mapping services. A lot of research efforts have been made to develop automatic reconstruction technique of large-scale 3D building models from remotely sensed data. However, existing methods still produce irregular building polygons due to errors induced partly by uncalibrated sensor system, scene complexity and partly inappropriate sensor resolution to observed object scales. Thus, a geometric regularization technique is urgently required to rectify such irregular building polygons that are quickly captured from low sensory data. This paper aims to develop a new method for regularizing noise building outlines extracted from airborne LiDAR data, and to evaluate its performance in comparison with existing methods. These include Douglas-Peucker's polyline simplication, total least-squared adjustment, model hypothesis-verification, and rule-based rectification. Based on Minimum Description Length (MDL) principal, a new objective function, Geometric Minimum Description Length (GMDL), to regularize geometric noises is introduced to enhance the repetition of identical line directionality, regular angle transition and to minimize the number of vertices used. After generating hypothetical regularized models, a global optimum of the geometric regularity is achieved by verifying the entire solution space. A comparative evaluation of the proposed geometric regulator is conducted using both simulated and real building vectors with various levels of noise. The results show that the GMDL outperforms the selected existing algorithms at the most of noise levels.

• Ecology and Resilient Infrastructure
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• 제8권4호
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• pp.204-211
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• 2021

본 연구에서는 3차원 지상 라이다 스캐너를 통해 수집되는 포인트 클라우드를 활용하여 식생의 정보를 수집하였으며, 수집된 데이터를 기반으로 객체를 재구현하여 물리적 형상을 분석하였다. 이를 위해 원시 데이터의 필터링 단계별 최적의 데이터를 구축하였으며, 구축된 데이터를 활용하여 실제 부피와 Alpha Shape 및 Voxel 기법을 활용한 부피 산정 결과를 산정한 후 각각 비교하였다. 분석 결과, Alpha Shape를 적용하여 부피를 산정한 경우 데이터 필터링과 관계없이 실제 부피보다 과다 산정되는 것으로 나타났다. 또한 Voxel 기법을 활용할 경우 8차 필터링 후 실제 부피와 가장 유사한 것으로 나타났으며, 이후 필터링이 진행될수록 실제 부피에 비해 과소 산정되는 것을 알 수 있었다. 따라서 포인트 클라우드를 활용하여 객체를 재구현 할 경우, 대상이 되는 객체의 복잡한 형상으로 인한 내부 공극을 고려해야 하며, 필터링 과정에서 최적의 데이터 구축을 위한 필터링 과정에 반드시 주의할 필요가 있다.

• 로봇학회논문지
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• 제7권2호
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• pp.92-100
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• 2012

A map of complex environment can be generated using a robot carrying sensors. However, representation of environments directly using the integration of sensor data tells only spatial existence. In order to execute high-level applications, robots need semantic knowledge of the environments. This research investigates the design of a system for recognizing objects in 3D point clouds of urban environments. The proposed system is decomposed into five steps: sequential LIDAR scan, point classification, ground detection and elimination, segmentation, and object classification. This method could classify the various objects in urban environment, such as cars, trees, buildings, posts, etc. The simple methods minimizing time-consuming process are developed to guarantee real-time performance and to perform data classification on-the-fly as data is being acquired. To evaluate performance of the proposed methods, computation time and recognition rate are analyzed. Experimental results demonstrate that the proposed algorithm has efficiency in fast understanding the semantic knowledge of a dynamic urban environment.

• 전기학회논문지
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• 제65권2호
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• pp.342-348
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• 2016

We propose an obstacle detection algorithm for unmanned ground vehicle on uneven terrain. The key ideas of the proposed algorithm are the use of two-layer laser range data to calculate the gradient of a target, which is characterized as either ground or obstacles. The proposed obstacle detection algorithm includes 4-steps: 1) Obtain the distance data for each angle from multiple lidars or a multi-layer scan lidar. 2) Calcualate the gradient for each angle of the uneven terrain. 3) Determine ground or obstacle for each angle on the basis of reference gradient. 4) Generate a new distance data for each angle for a virtual laser scanner. The proposed algorithm is verified by various experiments.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제23권10호
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• pp.588-593
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• 2017

본 논문에서는 자율주행차량에서 사용되는 고가의 다채널 라이다(LiDAR) 센서를 다수의 저가 소채널 라이다들로 대체하여 사용하는 경우에 다수의 라이다들을 하나의 라이다로 가상화하는 드라이버를 제안한다. 이를 통해 로봇 분야에서 하나의 물리 라이다를 가정하여 개발된 SLAM(Simultaneous Localization And Mapping) 알고리즘들은 수정 없이 사용될 수 있다. 본 논문은 제안하는 드라이버를 로봇운영체제 ROS(Robot Operating System) 상에서 구현하고 SLAM 알고리즘과 함께 평가하였다. 평가 결과, 제안한 드라이버는 3차원 점지도의 점밀도를 제어하는 필터와 함께 기존 알고리즘의 수정 없이 사용될 수 있음을 확인하였다.

• 한국건축시공학회지
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• 제23권3호
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• pp.273-284
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• 2023

건설프로젝트 진행 시 골조공사 후 시공상태를 점검하는 업무가 필수적이며, 이에 골조의 수직 및 수평 정확도를 점검하고 결함에 대한 보수작업을 수행한다. 하지만 기존의 업무방식은 점검자의 주관적 판단 및 인적오류의 발생 가능성으로 인한 신뢰성 문제, 수작업으로 인한 인력 및 시간 소모적 문제 등이 존재한다. 이에 본 연구는 상기 문제점을 해결하고, 골조공사 시공상태 점검 및 결과공유 과정의 효율을 높이고자 LiDAR 및 AR 기술의 활용방안을 제안하였다. 본 연구에서는 LiDAR를 통해 골조의 3D Point Cloud 데이터를 취득하여 시공상태 점검에 적용하는 방안과, 점검결과 데이터를 BIM 모델에 입력 후, AR을 통해 시각화하는 방안을 제안하였다. 이는 기존 방식 대비 점검과정의 객관성, 결과공유의 신속성 및 정확도 측면에서 효율적인 방식임을 확인하였으며, 더불어 건설프로젝트 전체의 품질 및 생산성 향상에 기여할수 있을 것으로 기대된다.