• Korean Journal of Remote Sensing
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• v.22 no.4
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• pp.265-274
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• 2006

Extracting ground points is the kernel of DTM generation being considered as one of the most popular LIDAR applications. The previous extraction approaches can be mostly characterized as a point based approach, which sequentially examines every individual point to determine whether it is measured from ground surfaces. The number of examinations to be performed is then equivalent to the number of points. Particularly in a large set, the heavy computational requirement associated with the examinations is obviously an obstacle to employing more sophisticated criteria for the examination. To reduce the number of entities to be examined and produce more robust results, we developed an approach based on features rather than points, where a feature indicates an entity constructed by grouping some points. In the proposed approach, we first generate a set of features by organizing points into surface patches and grouping the patches into surface clusters. Among these features, we then attempt to identify the ground features with the criteria based on the attributes of the features. The points grouped into these identified features are labeled ground points, being used for DTM generation afterward. The Proposed approach was applied to many real airborne LIDAR data sets. The analysis on the results strongly supports the prominent performance of the proposed approach in terms of not only the computational requirement but also the quality of the DTM.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.355-356
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• 2011

LiDAR data is very large, which contains an amount of redundant information. The information not only takes up a lot of storage space but also brings much inconvenience to the LIDAR data transmission and application. Therefore, a simplified method was proposed for LiDAR data based on quad-tree structure in this paper. The boundary contour lines of the buildings are displayed as building extraction. Experimental results show that the method is efficient for point's simplification according to the rule of mapping.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.93-97
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• 2024

With the development of promising future mobility and urban air mobility (UAM) technologies, the demand for LIDAR sensors has increased. The SWIR photodetector is a sensor that detects lasers for the 3D mapping of lidar sensor and is the most important technology of LIDAR sensor. An SWIR photodetector based on QDs in an eye-safe wavelength band of over 1400 nm has been reported. QDs-based SWIR photodetectors can be synthesized and processed through a solution process and have the advantages of low cost and simple processing. However, the organic ligands of QDs have insulating properties that limit their ability to improve the sensitivity and stability of photodetectors. Therefore, the technology to replace organic ligands with inorganic ligands must be developed. In this study, the organic ligand of the synthesized PbS QDs was replaced with a MAPI inorganic ligand, and an SWIR photodetector was fabricated. The analysis of the characteristics of the manufactured photodetector confirmed that the photodetector based on MAPI-capped PbS QDs exhibited up to 26.5% higher responsivity than that based on organic ligand PbS QDs.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.158-164
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• 2015

Lane detection is one of the key parts among autonomous vehicle technologies because lane keeping and path planning are based on lane detection. Camera is used for lane detection but there are severe limitations such as narrow field of view and effect of illumination. On the other hands, Lidar sensor has the merits of having large field of view and being little influenced by illumination because it uses intensity information. Existing researches that use methods such as Hough transform, histogram hardly handle multiple lanes in the co-occuring situation of lanes and road marking. In this paper, we propose a method based on RANSAC and regularization which provides a stable and precise detection result in the co-occuring situation of lanes and road marking in highway scenarios. This is performed by precise lane point extraction using circular model RANSAC and regularization aided least square fitting. Through quantitative evaluation, we verify that the proposed algorithm is capable of multi lane detection with high accuracy in real-time on our own acquired road data.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.267-279
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• 2015

In the development of autonomous vehicles, the importance of LIDAR sensors becomes larger. For sensor selection or algorithm development, it is difficult to test expensive LIDAR sensors mounted on a vehicle under various driving environment. In this study, we developed a simulator that is generally applicable for various vehicle LIDAR sensors based on the generalized geometric modeling of the common processes associated with vehicle LIDAR sensors. By configuring this simulator with the specific sensors being widely used, we performed the data simulation and quality analysis. Also, we applied the simulation data to obstacle detection and evaluated the applicability of the selected sensor. The developed simulator enables various experiments and algorithm development in parallel with hardware implementation prior to the deployment and operation of a sensor.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.313-320
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• 2018

The importance of sensors on a self-driving vehicle has rising since it act as eyes for the vehicle. Lidar sensors based on laser technology tend to yield better image quality with more laser channels, thus, it has higher detection accuracy for obstacles, pedistrians, terrain, and other vechicles. However, incorporating more laser channels results higher unit price more than ten times, and this is a major drawback for using high channel lidar sensors on a vehicle for actual consumer market. To come up with this drawback, we propose a method of integrating multiple low channel, low cost lidar sensors acting as one high channel sensor. The result uses four 16 channels lidar sensors with small form factor acting as one bulky 64 channels sensor, which in turn, improves vehicles cosmetic aspects and helps widespread of using the lidar technology for the market.

• Journal of the Optical Society of Korea
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• v.19 no.6
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• pp.695-699
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• 2015

A high spectral resolution lidar (HSRL) system based on injection-seeded Nd:YAG laser and iodine absorption filter has been developed for the quantitative measurement of aerosol and cloud. The laser frequency is stabilized at 80 MHz by a frequency locking system and the absorption line of iodine cell is selected at the 1111 line with 2 GHz width. The observations show that the HSRL can provide vertical profiles of particle extinction coefficient, backscattering coefficient and lidar ratio for cloud and aerosol up to 12 km altitude, simultaneously. For the measured cases, the lidar ratios are 10~20 sr for cloud, 28~37 sr for dust, and 58~70 sr for urban pollution aerosol. It reveals the potential of HSRL to distinguish the type of aerosol and cloud. Time series measurements are given and demonstrate that the HSRL has ability to continuously observe the aerosol and cloud for day and night.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.29-36
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• 2011

The main purpose of this paper is to make a map showing canopy cover by using airborne Lidar data based on region. Watershed algorithm was applied to elevation data to conduct segmentation, and then canopy cover was estimated through the regions extracted. In the process of transforming point data to raster, we solved the problems about overestimation and underestimation by using frequency method. Also, canopy cover map could be produced with various scales by differing level of segmentation and it provides more accurate and precise information than ones of ordinary public forest map.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1846-1856
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• 2016

This study proposes a novel feature point initialization method in order to improve the accuracy of feature point positions by fusing a vision sensor and a lidar. The initialization is a process that determines three dimensional positions of feature points through two dimensional image data, which has a direct influence on performance of a 6-DoF bearing-only SLAM. Prior to the initialization, an extrinsic calibration method which estimates rotational and translational relationships between a vision sensor and lidar using multiple calibration tools was employed, then the feature point initialization method based on the estimated extrinsic calibration parameters was presented. In this process, in order to improve performance of the accuracy of the initialized feature points, an iterative automatic scaling parameter tuning technique was presented. The validity of the proposed feature point initialization method was verified in a 6-DoF bearing-only SLAM framework through an indoor and outdoor tests that compare estimation performance with the previous initialization method.

• The Journal of Korea Robotics Society
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• v.9 no.3
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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.