• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.170-178
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• 2019

This paper proposes a parking space detection method for autonomous parking by using the Around View Monitor (AVM) image and Light Detection and Ranging (LIDAR) sensor fusion. This method consists of removing obstacles except for the parking line, detecting the parking line, and template matching method to detect the parking space location information in the parking lot. In order to remove the obstacles, we correct and converge LIDAR information considering the distortion phenomenon in AVM image. Based on the assumption that the obstacles are removed, the line filter that reflects the thickness of the parking line and the improved radon transformation are applied to detect the parking line clearly. The parking space location information is detected by applying template matching with the modified parking space template and the detected parking lines are used to return location information of parking space. Finally, we propose a novel parking space detection system that returns relative distance and relative angle from the current vehicle to the parking space.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.480-488
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• 2019

In this paper, we propose an obstacle avoidance system for an unmanned ship to navigate safely in dynamic environments. Also, in this paper, one-dimensional low-cost lidar sensor is used, and a servo motor is used to implement the lidar sensor in a two-dimensional space. The distance and direction of an obstacle are measured through the two-dimensional lidar sensor. The unmanned ship is controlled by the application at a Tablet PC. The user inputs the coordinates of the destination in Google maps. Then the position of the unmanned ship is compared with the position of the destination through GPS and a geomagnetic sensor. If the unmanned ship finds obstacles while moving to its destination, it avoids obstacles through a fuzzy control-based algorithm. The paper shows that the experimental results can effectively construct an obstacle avoidance system for an unmanned ship with a low-cost LiDAR sensor using fuzzy control.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.1-9
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• 2012

The diurnal variation in pollen vertical distributions in the atmosphere was observed by a surface-based lidar remote sensing technique. Aerosol extinction coefficient and depolarization ratio at 532 nm were obtained from lidar measurements in spring ($4^{th}$ May - $2^{nd}$ June) 2009 at Gwangju Institute of Science & Technology (GIST) located in Gwangju, Korea ($35.15^{\circ}E$, $126.53^{\circ}N$). Unusual variations of depolarization ratio were observed for six days from $4^{th}$ to $9^{th}$ May. Depolarization ratios varied from 0.08 to 0.14 were detected at the low altitude in the morning. The altitude with those high depolarization ratios was increased up to 1.5 - 2.0 km at the time interval between 12:00 and 14:00 LT and then decreased. The temporal variations in high values of depolarization ratios from lidar measurements show good agreement in patterns with the sampled pollen concentrations measured using the Burkard trap sampler. This study demonstrates that the pollen distribution data obtained by lidar measurements can be a useful tool for investigating spatial and temporal characteristic of pollen particles.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.8-15
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• 2011

In this paper, we propose a new structure modeling algorithm from 3D cloud points of terrestrial LADAR data. Terrestrial LIDAR data have various obstacles which make it difficult to apply conventional algorithms designed for air-borne LIDAR data. In the proposed algorithm, the field data are separated into several clusters by adopting the structure extraction method which uses color information and Hough transform. And cluster based Delaunay triangulation technique is sequentially applied to model the artificial structure. Each cluster has its own priority and it makes possible to determine whether a cluster needs to be considered not. The proposed algorithm not only minimizes the effects of noise data but also interactively controls the level of modeling by using cluster-based approach.

• Korean Journal of Optics and Photonics
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• v.33 no.1
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• pp.1-10
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• 2022

In this study we introduce a new method for high-spatial-resolution continuous wave (CW) aerosol lidar that has a high spatial resolution in the near field and a low spatial resolution at long distances. A normal lidar system uses a nanosecond-pulse laser and measures the round-trip TOF between the aerosol and laser to obtain range resolution. In this study, however, we propose a new type of spatially resolving aerosol lidar that uses laser-scattering images. Using a laser-light-scattering image, we have calculated the distance of each scattering aerosol image for a given pixel, and recovered the short-range aerosol extinction. For this purpose, we have calculated the distance image and the contribution range of the aerosol to the given one-pixel image, and finally we have calculated the extinction coefficients of the aerosol with range-resolved information. In the case of traditional aerosol lidar, we can only obtain the aerosol extinction coefficients above 400 m. Using our suggested method, it was possible to extend the range of the extinction coefficient lower then several tens of meters. Finally, we can remove the unknown short-range region of pulsed aerosol lidar using our method.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.179-182
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• 2007

In this study, we proposed a way to detect trees using virtual grid and to discriminate vertical wall points from building tops based on effective segmentation of LIDAR point cloud utilizing scan line characteristics. Trees were detected by their surface roughness value calculated based on virtual grid and vertical building wall points were discriminated from building tops with one dimensional filtering of scan line during segmenting point cloud. In results, we could distinguish trees from buildings and bind virtical wall points to prevent them from faltly acting on point segmentation process.

• Journal of Auto-vehicle Safety Association
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• v.9 no.4
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• pp.32-37
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• 2017

For automated vehicles, the integrity and fault tolerance of environment perception sensor have been an important issue. This paper presents radar, vision, lidar(laser radar) fusion-based fault detection algorithm for autonomous vehicles. In this paper, characteristics of each sensor are shown. And the error of states of moving targets estimated by each sensor is analyzed to present the method to detect fault of environment sensors by characteristic of this error. Each estimation of moving targets isperformed by EKF/IMM method. To guarantee the reliability of fault detection algorithm of environment sensor, various driving data in several types of road is analyzed.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.227-229
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• 2010

This study presents an application of the 3D patch extraction method which is based on gradient-driven properties to obtain 3D planar patches over the terrain and man-made objects from lidar data. The method which was exploited in this study is composed of a sequence of processes: segmentation by slope, initiation of triggering patches by mode selection, and expansion of the triggering patches. Since urban areas contain many planar regions over the terrain surface, application of the method has been experimented to extract 3D planar patches not only from non-terrain objects but also from the terrain. The experimental result shows that the method is efficient to acquire 3D planar patches.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.02a
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• pp.73-81
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• 2004

National Geographic Information Institute (NGII) in Korea, through National Geographic Information System (NGIS) Program, has prepared to generate and disseminate digital elevation data for Korea. This is a pilot research to propose a policy for generation, maintenance, and supply of Korea Digital Elevation Data (KDED). Customer demands for accuracy and resolution of DEM was surveyed through questionnaire. In order to investigate the quality, the technical efficiency and the production cost, a tentative DEM in a small test site was generated based on digital topographic maps (original paper map scale 1 :5,000), analytical plotter, and LIDAR. Accuracy standard for KDED was derived based on source data and generation methods. As results of this research, we recommend uniformly spaced grid model for KDED. Its preferable grid space is 5m in urban and its vicinity; and 10m in field and mountainous area. LIDAR has been valuated as a proper KDED generation method fulfilling customers demand for the accuracy.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.23-30
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• 2020

Recently, self-driving research has been actively studied in various institutions. Accurate recognition is important because information about surrounding objects is needed for safe autonomous driving. This study mainly deals with the signal processing of LiDAR among sensors for object recognition. LiDAR is a sensor that is widely used for high recognition accuracy. First, we clustered and tracked objects by predicting relative position and speed of objects. The characteristic points of all objects were extracted using point cloud data of each objects through proposed algorithm. The Classification between vehicle and pedestrians is estimated using number of characteristic points and distances among characteristic points. The algorithm for classifying cars and pedestrians was implemented and verified using test vehicle equipped with LiDAR sensors. The accuracy of proposed object classification algorithm was about 97%. The classification accuracy was improved by about 13.5% compared with deep learning based algorithm.