• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.427-433
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• 2022

Obstacle detection, collision recognition, and avoidance technologies are required the collision avoidance technology for UAVs. In this paper, considering collinear multiple static obstacle, we propose an obstacle detection algorithm using LiDAR and a collision recognition and avoidance algorithm based on CPA. Preprocessing is performed to remove the ground from the LiDAR measurement data before obstacle detection. And we detect and classify obstacles in the preprocessed data using the K-means clustering algorithm. Also, we estimate the absolute positions of detected obstacles using relative navigation and correct the estimated positions using a low-pass filter. For collision avoidance with the detected multiple static obstacle, we use a collision recognition and avoidance algorithm based on CPA. Information of obstacles to be avoided is updated using distance between each obstacle, and collision recognition and avoidance are performed through the updated obstacles information. Finally, through obstacle location estimation, collision recognition, and collision avoidance result analysis in the Gazebo simulation environment, we verified that collision avoidance is performed successfully.

• Journal of Korean Society of Forest Science
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• v.85 no.3
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• pp.539-551
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• 1996

In this study, a number of distance-dependent competition indices on tree-level which incorporate the tree sizes and distances to competitors, and traditional stand-level density measures were estimated from the data compiled with position-dependent survey in a Pinus densiflora stand. The performance of the estimated competition indices was examined by comparing the relationship with the diameter growth, and a dbh growth function, in which the competition index is considered as a one of influence factors, are developed. In the searching method of competing trees, the competition index estimated with $30^{\circ}$ competition interrupting angle showed the highest correlation with the annual dbh growth, while the expanding the competing zone distance had no significant effect on the performance of competition index in estimating annual dbh growth. The most of the examined stand-level competition indices, based on distance-dependent single-tree competition indices, were evaluated to describe similarly the stand competition status. As a result of partial correlation analysis in which the effect of age and site index are eliminated, Alemdag's mean competition index and relative spacing index were determined to have the highest correlation with dbh. The relative spacing index, which can be easily measured in field without measuring the position of individual trees, was considered to be a better suited one for estimating mean dbh of a stand. Among distance-dependent competition indices on tree-level, Hegyi's competition index showed the best performance in their correlation with annual dbh growth, if eliminated the effect of site index and dbh. This enabled to derive the following annual dbh growth function of individual trees which incorporate age, dominant height, dbh and Hegyi's competition index as influence factors : $$dbh^{\prime}=3.975362676{\cdot}age^{-1.099274613}{\cdot}ho^{0.199893990}{\cdot}dbh^{0.269430865}{\cdot}HgCI^{-0.353643587}$$ This function is coincided to the growth principle in which site index has a positive effect on the annual dbh growth, while high age or competition causes to reduce the annual dbh growth, and can be used as a function in single tree growth model.

• Journal of the Korean Geotechnical Society
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• v.20 no.2
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• pp.131-141
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• 2004

For geotechnical applications, engineers use data obtained from a site investigation to interpret the structure and potential behavior of the subsurface. In most cases, these data consist of samples that represent 1/100,000 or less of the total volume of soil. These samples and associated field and lab testing provide the information used to estimate soil parameter values. The resulting values are estimated ones and there exists some likelihood that actual soil conditions are significantly different from the estimates. This may be the case even if the sampling and interpretation procedures are performed in accordance with standard practice. Although these efforts have been made to characterize the uncertainty associated with geotechnical parameters, there is no commonly accepted method to evaluate quantitatively the quality of an investigation plan as a whole or the relative significance of individual sampling points or potential sampling points.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.53-53
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• 2022

본 연구는 낙동강 상류에 위치한 안동댐 하류(4,565.7 km²)를 대상으로 1차원 물리적 서식처모형인 PHABSIM(Physical Habitat Simulation System)과 2차원 물리적 서식처 모형인 River2D를 이용하여 대표어종인 피라미에 대해 환경생태유량과 어류서식처 면적을 산정하였다. 두 모형의 구축을 위해 낙동강 하천기본계획보고서(2009)를 수집하여 하천단면과 수리학적 자료를 두 서식처모형에 적용하였다. 유속과 수위자료의 경우, 낙동강수문조사연보와 검보정된 HEC-RAS를 활용하여 갈수량 Q355(10.95 m³/sec)와 평수량 Q185(41.72 m³/sec)에서의 유속과 수위를 생성하여 적용하였다. 대표어종 선정을 위해 총 4회에 걸쳐 현장조사를 진행하였으며, 수집한 어종들에 대해 상대풍부도와 출현 개체수 분석결과 54.2%의 상대풍부도와 총 110개의 개체수를 나타낸 피라미(Z acco platypus)를 대표어종으로 선정하였다. 서식처 적합도 지수 HSI(Habitat Suitability Index)는 피라미 출현시기의 수심(Depth), 유속(Velocity) 그리고 하상재료(Substrate)를 조사하여 적립하였으며 수심은 0.4~0.6 m, 유속은 0.3~0.5 m/s, 하상재료는 모래(2.0 mm)~잔자갈(16.0 mm)일 때 HSI가 가장 적합한 것으로 분석되었다. PHABSIM을 이용하여 피라미에 대해 최적 환경생태유량 산정결과 20.0 m³/sec로 산정되었고, 모의한 30개 유량에 대해 평균 어류서식처 면적은31,905.3 m²/1,000m로 산정되었다. PHABSIM으로 산정된 환경생태유량과 River2D를 이용하여 하천유량이 Q355와 환경생태유량일 때의 공간분석을 실시하였다. Q355와 비교하여 환경생태유량일 때 유속과 수심 HSI에 대한 공간분포와 어류서식처 면적 또한 더 큰 것으로 분석되었다.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.95-104
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• 2012

Although the educational institutions of computers have evolved to train students in pace with the changes of computing, many students still believe that computer programming is hard to be mastered. The reluctance of students toward programming languages have been tied to the decrease of computer-related majors and now many countries are in short of computer programmers. By investigating the similarities among eleven popular programming languages, this research is intended to measure the relative distances and understand the dimensions that scattered the languages.

• Journal of Sensor Science and Technology
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• v.29 no.4
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• pp.237-242
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• 2020

This paper deals with relative position estimation using a Kalman filter (KF) based on inertial sensors that have been widely used in various biomechanics-related outdoor applications. In previous studies, the relative position is determined using relative orientation and predetermined segment-to-joint (S2J) vectors, which are assumed to be constant. However, because body segments are influenced by soft tissue artifacts (STAs), including the deformation and sliding of the skin over the underlying bone structures, they are not constant, resulting in significant errors during relative position estimation. In this study, relative position estimation was performed using a KF, where the S2J vectors were adopted as time-varying states. The joint constraint and the variations of the S2J vectors were used to develop a measurement model of the proposed KF. Accordingly, the covariance matrix corresponding to the variations of the S2J vectors continuously changed within the ranges of the STA-causing flexion angles. The experimental results of the knee flexion tests showed that the proposed KF decreased the estimation errors in the longitudinal and lateral directions by 8.86 and 17.89 mm, respectively, compared with a conventional approach based on the application of constant S2J vectors.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.931-938
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• 2008

In this paper, a novel localization algorithm robust to the unmodeled systematic odometry errors is proposed for low-cost non-holonomic mobile robots. It is well known that the most pose estimators using odometry measurements cannot avoid the performance degradation due to the dead-reckoning of systematic odometry errors. As a remedy for this problem, we tty to reflect the wheelbase error in the robot motion model as a parametric uncertainty. Applying the Krein space estimation theory for the discrete-time uncertain nonlinear motion model results in the extended robust Kalman filter. This idea comes from the fact that systematic odometry errors might be regarded as the parametric uncertainties satisfying the sum quadratic constrains (SQCs). The advantage of the proposed methodology is that it has the same recursive structure as the conventional extended Kalman filter, which makes our scheme suitable for real-time applications. Moreover, it guarantees the satisfactoty localization performance even in the presence of wheelbase uncertainty which is hard to model or estimate but often arises from real driving environments. The computer simulations will be given to demonstrate the robustness of the suggested localization algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.8
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• pp.759-766
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• 2009

The purpose of this paper is an image processing algorithm development as a base research achieving performance enhancement of integrated navigation system. We used the SIFT (Scale Invariant Feature Transform) algorithm for image processing, and developed feature point matching filter for rejecting mismatched points. By applying the proposed algorithm, it is obtained better result than other methods of parameter tuning and KLT based feature point tracking. For further study, integration with INS and algorithm optimization for the real-time implementation are under investigation.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.55-64
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• 2010

In order to prepare an efficient solution for PM10 reduction in underground stations, the authors measured PM10 concentration levels every 30 minutes in the concourse, platform, and tunnel of Gaehwasan Station of Seoul's subway line 5. Through a correlation analysis of each changing pattern of PM10 concentration, the direction and velocity of diffusion in underground stations were estimated. The PM10 concentration levels were highest in the tunnel, followed by the platform and concourse. PM10 concentrations in the tunnel, platform, and concourse showed a pattern of increasing in the rush hours and decreasing in the non-rush hours. According to the statistical analysis of PM10 concentrations and changing patterns in each location, the higher PM10 concentration in the tunnel expanded to the platform, and some from the platform expanded to the concourse. Therefore, to efficiently reduce PM10 concentrations, it is essential to detect the centralized generation, diffusion factor, expanding route, expanding measure, and other variables and to remove or reduce the diffusion factor and level. Through operating the ventilation system in the right time frame while the PM10 concentration level increases, the power consumption and peak power consumption can be reduced.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.421-433
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• 2006

This paper proposes a method to insert virtual objects into a real video stream based on feature tracking and camera pose estimation from a set of single-camera video frames. To insert or modify 3D shapes to target video frames, the transformation from the 3D objects to the projection of the objects onto the video frames should be revealed. It is shown that, without a camera calibration process, the 3D reconstruction is possible using multiple images from a single camera under the fixed internal camera parameters. The proposed approach is based on the simplification of the camera matrix of intrinsic parameters and the use of projective geometry. The method is particularly useful for augmented reality applications to insert or modify models to a real video stream. The proposed method is based on a linear parameter estimation approach for the auto-calibration step and it enhances the stability and reduces the execution time. Several experimental results are presented on real-world video streams, demonstrating the usefulness of our method for the augmented reality applications.