• ETRI Journal
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• 제33권4호
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• pp.506-516
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• 2011

In this paper, we develop a registration method to eliminate the geometric inconsistency between the stereo-images and light detection and ranging (LIDAR) data obtained by an airborne multisensor system. This method consists of three steps: registration primitive extraction, correspondence establishment, and exterior orientation parameter (EOP) adjustment. As the primitives, we employ object points and linked edges from the stereo-images and planar patches and intersection edges from the LIDAR data. After extracting these primitives, we establish the correspondence between them, being classified into vertical and horizontal groups. These corresponding pairs are simultaneously incorporated as stochastic constraints into aerial triangulation based on the bundle block adjustment. Finally, the EOPs of the images are adjusted to minimize the inconsistency. The results from the application of our method to real data demonstrate that the inconsistency between both data sets is significantly reduced from the range of 0.5 m to 2 m to less than 0.05 m. Hence, the results show that the proposed method is useful for the data fusion of aerial images and LIDAR data.

• 한국측량학회지
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• 제38권5호
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• pp.425-433
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• 2020

Three-dimensional data has been used for different applications such as robotics, building reconstruction, and so on. 3D data can be generated from an optical camera or a laser scanner. Especially, a wearable multi-sensor system including the above-mentioned sensors is an optimized structure that can overcome the drawbacks of each sensor. After finding the geometric relationships between sensors, georeferencing of the datasets acquired from the moving system, should be carried out. Especially, in an indoor environment, error propagation always causes problem in the georeferencing process. To improve the accuracy of this process, other sources of data were used to combine with LiDAR (Light Detection and Ranging) data, and various registration methods were also tested to find the most suitable way. More specifically, this paper proposed a new process of NDT (Normal Distribution Transform) to register the LiDAR point cloud, with additional information from other sensors. For real experiment, a wearable mapping system was used to acquire datasets in an indoor environment. The results showed that applying the new process of NDT and combining LiDAR data with IMU (Inertial Measurement Unit) information achieved the best result with the RMSE 0.063 m.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.113-119
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• 2003

Building information is extremely important for many applications within the urban environment. Sufficient techniques and user-friendly tools for information extraction from remotely sensed imagery are urgently needed. This paper presents an automatic and manual approach for extracting footprints of buildings in urban areas from airborne Light Detection and Ranging (LIDAR) data. First a digital surface model (DSM) was generated from the LIDAR point data. Then, objects higher than the ground surface are extracted using the generated DSM. Based on general knowledge on the study area and field visits, buildings were separated from other objects. The automatic technique for extracting the building footprints was based on different window sizes and different values of image add backs, while the manual technique was based on image segmentation. A comparison was then made to see how precise the two techniques are in detecting and extracting building footprints. Finally, the results were compared with manually digitized building reference data to conduct an accuracy assessment and the result shows that LIDAR data provide a better shape characterization of each buildings.

• 로봇학회논문지
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• 제9권3호
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• pp.154-159
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• 2014

The Global Positioning System (GPS) is widely used to aid the navigation of aerial vehicles. However, the GPS cannot be used indoors, so alternative navigation methods are needed to be developed for micro aerial vehicles (MAVs) flying in GPS-denied environments. In this paper, a real-time three-dimensional (3-D) indoor navigation system and closed-loop control of a quad-rotor aerial vehicle equipped with an inertial measurement unit (IMU) and a low-cost light detection and ranging (LIDAR) is presented. In order to estimate the pose of the vehicle equipped with the two-dimensional LIDAR, an octree-based grid map and Monte-Carlo Localization (MCL) are adopted. The navigation results using the MCL are then evaluated by making a comparison with a motion capture system. Finally, the results are used for closed-loop control in order to validate its positioning accuracy during procedures for stable hovering and waypoint-following.

• 한국측량학회지
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• 제37권5호
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• pp.397-402
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• 2019

Recently, with the emergence of autonomous vehicles and the increasing interest in safety, a variety of research has been being actively conducted to precisely estimate the position of a vehicle by fusing sensors. Previously, researches were conducted to determine the location of moving objects using GNSS (Global Navigation Satellite Systems) and/or IMU (Inertial Measurement Unit). However, precise positioning of a moving vehicle has lately been performed by fusing data obtained from various sensors, such as LiDAR (Light Detection and Ranging), on-board vehicle sensors, and cameras. This study is designed to enhance kinematic vehicle positioning performance by using feature-based recognition. Therefore, an analysis of the required precision of the observations obtained from the images has carried out in this study. Velocity and attitude observations, which are assumed to be obtained from images, were generated by simulation. Various magnitudes of errors were added to the generated velocities and attitudes. By applying these observations to the positioning algorithm, the effects of the additional velocity and attitude information on positioning accuracy in GNSS signal blockages were analyzed based on Kalman filter. The results have shown that yaw information with a precision smaller than 0.5 degrees should be used to improve existing positioning algorithms by more than 10%.

• 신재생에너지
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• 제18권1호
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• pp.1-16
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• 2022

Climatic characteristics were described using the LiDAR (Light Detection and Ranging) and the met-mast on Dongbok·Bukchon region. The influences of meteorological conditions on the power performance of wind turbines were presented using the data of Supervisory Control And Data Acquisition (SCADA) and met-mast of the Dongbok·Bukchon Wind Farm (DBWF) located in Jeju Island. The stability was categorized into three parameters (Richardson number, Turbulence intensity, and Wind shear exponent). DBWF was dominant in unstable atmospheric conditions. At wind speeds of 14 m/s or more, the proportion of slightly unstable conditions accounted for more than 50%. A clear difference in the power output of the wind turbine was exhibited in the category of atmospheric stability and turbulence intensity (TI). Particularly, a more sensitive difference in power performance was showed in the rated wind speeds of the wind turbine and wind regime with high TI. When the flow had a high turbulence at low wind speeds and a low turbulence at rated wind speeds, a higher wind energy potential was produced than that in other conditions. Finally, the high-efficiency of the wind farm was confirmed in the slightly unstable atmospheric stability. However, when the unstable state become stronger, the wind farm efficiency was lower than that in the stable state.

• 대기
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• 제28권1호
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• pp.1-13
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• 2018

Characteristics of wind resources of offshore and coastal regions were compared using wind data obtained from HeMOSU-1 (Herald of Meteorological and Oceanographic Special Unit-1) meteorological mast located at Southwestern Sea, and ground-based LiDAR (Light Detection And Ranging) at Gochang observation site near it. The analysis includes comparison of basic wind statistics such as mean wind speed, wind direction, power law exponent and their temporal variability as well as site assessment items for the wind power plant such as turbulence intensity and wind power density at the two observation sites. It was found that the wind at HeMOSU-1 site has lower diurnal and seasonal variability than that at Gochang site, which lead to smaller turbulence intensity. Overall, the results of the comparative analysis show that the wind resource at HeMOSU-1 site located offshore has more favorable condition for wind power generation than the wind resource at Gochang which shows nature of coastal area.

• 한국대기환경학회지
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• 제28권2호
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• pp.159-171
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• 2012

Aerosol direct radiative forcing (ADRF) retrieval method was developed by combining data from passive and active satellite sensors. Aerosol optical thickness (AOT) retrieved form the Moderate Resolution Imaging Spectroradiometer (MODIS) as a passive visible sensor and aerosol vertical profile from to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) as an active laser sensor were investigated an application possibility. Especially, space-born Light Detection and Ranging (Lidar) observation provides a specific knowledge of the optical properties of atmospheric aerosols with spatial, temporal, vertical, and spectral resolutions. On the basis of extensive radiative transfer modeling, it is demonstrated that the use of the aerosol vertical profiles is sensitive to the estimation of ADRF. Throughout the investigation of relationship between aerosol height and ADRF, mean change rates of ADRF per increasing of 1 km aerosol height are smaller at surface than top-of-atmosphere (TOA). As a case study, satellite data for the Asian dust day of March 31, 2007 were used to estimate ADRF. Resulting ADRF values were compared with those retrieved independently from MODIS only data. The absolute difference values are 1.27% at surface level and 4.73% at top of atmosphere (TOA).

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.453-464
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• 2012

This is a research of an adaptive longitudinal control system for situated cognition in wide range, traffic accidents reduction and safety driving environment by integrated system which graft a road infrastructure's information based on IT onto the intelligent vehicle combined automobile and IT technology. The road infrastructure installed by laser scanner in intersection, speed limited area and sharp curve area where is many risk of traffic accident. The road infra conducts objects recognition, segmentation, and tracking for determining dangerous situation and communicates real-time information by Ethernet with vehicle. Also, the data which transmitted from infrastructure supports safety driving by integrated with laser scanner's data on vehicle bumper.

• 한국측량학회지
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• 제24권2호
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• pp.209-215
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• 2006

해안선은 자연적, 인위적 행위에 의해 끊임없이 그 형상과 특징이 변화하며, 국토를 규정하는 중요한 정보이다. 이러한 해안선은 해양지리정보체계에서 기본정보(Framework Data)로 활용이 되며, 해안 지역의 모니터링 체계를 구축하는데 있어서 그 중요성이 날로 증가하고 있는 실정이다. 본 연구에서는 최근 개발되어 해양 및 해안 분야에 적용되고 있는 LiDAR 데이터를 이용하여 자동으로 해안선을 추출할 수 있는 알고리즘을 제안하고 그 결과를 지상측량을 통해 얻어진 해안선과 비교하였다. 본 연구의 제안한 알고리즘을 적용하여 항공 LiDAR 데이터를 이용한 해안선을 추출한 결과, 인공 및 자연 해안지역 등 다양한 지형에서 현행 지상측량과 비교를 하였을 때, 안정된 결과를 도출하였으며, 항공 LiDAR 데이터를 이용하여 효율적인 해안선 추출의 가능성을 보여주었다.