• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.702-704
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• 2022

자율주행 시뮬레이터를 위한 대체재로 게임 엔진을 통한 가상 환경 모의 연구가 수행되고 있다. 하지만 게임 엔진에서는 자율 주행에 필요한 센서를 기기에 맞게 사용자가 직접 모델링을 해줘야 하기 때문에 개발 비용이 크게 작용된다. 특히, Ray 를 활용한 3D LIDAR 는 GPU(Graphics Processing Unit) 사용량이 많은 작업이기 때문에 저비용 시뮬레이터를 위해서는 저비용 3D LIDAR 모의가 필요하다. 본 논문에서는 낮은 컴퓨터 연산을 사용하는 C++ 기반 3D LIDAR 모의 프레임 워크를 제안한다. 제안된 3D LIDAR 는 다수의 언덕으로 이루어진 비포장 Map 에서 성능을 검증 하였으며, 성능 검증을 의해 본 논문에서 생성된 3D LIDAR 로 간단한 LPP(Local Path Planning) 생성 방법도 소개한다. 제안된 3D LIDAR 프레임 워크는 저비용 실시간 모의가 필요한 자율 주행 분야에 적극 활용되길 바란다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.231-233
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• 2010

Many algorithms for processing LIDAR data are being developed for diverse applications not limited to patch segmentation, bare-earth filtering and building extraction. However, since we cannot exactly know the true locations of LIDAR points, it is difficult to assess the performance of a LIDAR data processing algorithm. In this paper, we thus attempted the performance assessment of the segmentation algorithm developed by Lee (2006) using the LIDAR data generated through simulation based on sensor modelling. Consequently, based on simulation, we can perform the performance assessment of a LIDAR processing algorithm more objectively and quantitatively with an automatic procedure.

• Journal of the Korean Solar Energy Society
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• v.37 no.5
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• pp.1-11
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• 2017

A study on Nacelle Lidar (Light detection and ranging) measurement error and the data reliability verification was carried out at Haengwon wind farm on Jeju Island. For measurement data error processing, the characteristics of Nacelle Lidar measurements were analyzed by dividing into three parts, which are weather conditions (temperature, humidity, atmosphere, amount of precipitation), mechanical movement (rotation of wind turbine blades, tilt variation of Nacelle Lidar) and Nacelle Lidar data availability. After processing the measurement error, the reliability of Nacelle Lidar data was assessed by comparing with wind data by an anemometer on a met mast, which is located at a distance of 200m from the wind turbine with Nacelle Lidar. As a result, various weather conditions and mechanical movement did not disturb reliable data measurement. Nacelle Lidar data with availability of 95% or more could be used for checking Nacelle Lidar wind data reliability. The reliability of Nacelle Lidar data was very high with regression coefficient of 98% and coefficient of determination of 97%.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.119-129
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• 2010

Many algorithms for processing LIDAR data have been developed for diverse applications not limited to patch segmentation, bare-earth filtering and building extraction. However, since we cannot exactly know the true locations of individual LIDAR points, it is difficult to assess the performance of a LIDAR data processing algorithm. In this paper, we thus attempted the performance assessment of the segmentation algorithm developed by Lee (2006) using the LIDAR data generated through simulation based on sensor modelling. Consequently, based on simulation, we can perform the performance assessment of a LIDAR processing algorithm more objectively and quantitatively with an automatic procedure.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1309-1312
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• 2015

본 논문에서는 현대 자율 주행 차량 경진대회에 적용되었던 LIDAR 기반의 다중 물체 추적 알고리즘을 소개한다. 물체 추적은 자율 주행 차량이 외부 환경을 인지하는데 중요한 역할을 한다. 본 논문의 물체 추적 알고리즘은 동시에 여러 개의 물체를 추적할 수 있도록 Multiple Data Association 방식을 사용하였고 순수하게 LIDAR만으로 동작하기 때문에 밤과 낮 모든 경우에 적용 가능하다. 알고리즘은 Clustering, Data Association, State Estimation, Data Arrangement 총 4단계로 이루어져 있으며 본 논문에서는 각 단계별로 알고리즘의 동작 방식을 소개한다. 실제 구현에는 Velodyne사의 HDL-32e이 사용되었고 실제 주행에서 교차로 내의 차량 추적 및 선행 차량의 동향을 추적하는데 적용되었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.80-83
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• 2019

지능형 로봇 기술은 더 나은 생활을 위한 현대 기술의 집약체이다. 산업, 생활, 정밀 기술 등 다양한 분야에서 응용이 가능한 확장성 넓은 분야이다. 해당 분야의 추적 기술은 LIDAR를 활용하는 방향으로 활발한 연구가 진행 중이다. LIDAR는 사방의 거리를 정확하게 측정할 수 있는 유용한 센서지만, LIDAR만으로는 로봇의 성능을 최대화할 수는 없다. 본 논문은 LIDAR 추적을 연장하여 Vision 기술의 융합에 관련하여 서술한다. Vision 기술의 융합을 통한 향상된 기능을 가지는 추적 로봇 설계 방법을 제안한다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.637-641
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• 2007

Airborne LIDAR (Light Detection and Ranging) technology has reached a degree of the required accuracy in mapping professions, and advanced LIDAR systems are becoming increasingly common in the various fields of application. LiDAR data constitute an excellent source of information for reconstructing the Earth's surface due to capability of rapid and dense 3D spatial data acquisition with high accuracy. However, organizing the LIDAR data and extracting information from the data are difficult tasks because LIDAR data are composed of randomly distributed point clouds and do not provide sufficient semantic information. The main reason for this difficulty in processing LIDAR data is that the data provide only irregularly spaced point coordinates without topological and relational information among the points. This study introduces an efficient and robust method for automatic extraction of building footprints using airborne LIDAR data. The proposed method separates ground and non-ground data based on the histogram analysis and then rearranges the building boundary points using convex hull algorithm to extract building footprints. The method was implemented to LIDAR data of the heavily built-up area. Experimental results showed the feasibility and efficiency of the proposed method for automatic producing building layers of the large scale digital maps and 3D building reconstruction.

• Tunnel and Underground Space
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• v.19 no.1
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• pp.1-10
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• 2009

Site characterization for structural stability in rock masses mainly involves the collection of joint property data, and in the current practice, much of this data is collected by hand directly at exposed slopes and outcrops. There are many issues with the collection of this data in the field, including issues of safety, slope access, field time, lack of data quantity, reusability of data and human bias. It is shown that information on joint orientation, spacing and roughness in rock masses, can be automatically extracted from LIDAR (light detection and ranging) point floods using the currently available Split-FX point cloud processing software, thereby reducing processing time, safety and human bias issues.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.10-11
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• 2015

최근 자율 주행 분야의 연구에서 LIDAR를 활용한 분류 기법들이 연구되고 있다. 그러나 2D 영상 처리와 비교하여, 대량의 3D 포인트를 사용하는 분류 알고리즘의 성능을 평가하기 위한 지상 검증자료를 쉽게 획득하기 어렵다. 본 연구는 LIDAR를 가상 공간에서 시뮬레이션 함으로써 감지한 물체의 정보를 기록함으로써 3D 포인트 클라우드를 사용하는 다양한 분류 알고리즘의 검증을 위한 지상검증자료를 생성하는 기법을 설명한다. 본 기법은 실제 LIDAR를 사용하는 것보다 적은 비용으로 다양한 환경에서의 분류 알고리즘 성능 검증을 가능하게 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.28-34
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• 2020

This paper proposes an approach to the fusion of two heterogeneous sensors with two different fields-of-view (FOV): LIDAR and an RGB camera. Registration between data captured by LIDAR and an RGB camera provided the fusion results. Registration was completed once a depthmap corresponding to a 2-dimensional RGB image was generated. For this fusion, RPLIDAR-A3 (manufactured by Slamtec) and a general digital camera were used to acquire depth and image data, respectively. LIDAR sensor provided distance information between the sensor and objects in a scene nearby the sensor, and an RGB camera provided a 2-dimensional image with color information. Fusion of 2D image and depth information enabled us to achieve better performance with applications of object detection and tracking. For instance, automatic driver assistance systems, robotics or other systems that require visual information processing might find the work in this paper useful. Since the LIDAR only provides depth value, processing and generation of a depthmap that corresponds to an RGB image is recommended. To validate the proposed approach, experimental results are provided.