• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.92-94
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• 2005

Unmanned ground vehicles(UGVs) are expected to play a key role in the future army. These UGVs would be used for weapons platforms. logistics carriers, reconnaissance, surveillance, and target acquisition in the rough terrain. Most of path planning methodologies for UGVs offer an optimal or sub-optimal shortest-path in a 20 space. However, those methodologies do not consider increment and reduction effects of relative distance when a UGV climbs up or goes down in the slope of rough terrain. In this paper, we propose a novel path planning methodology using the modified distance transform algorithm. Our proposed path planning methodology employs two kinds of map. One is binary obstacle map. The other is the DEM. With these two maps, the modified distance transform algorithm in which distance between cells is increased or decreased by weighting function of slope is suggested. The proposed methodology is verified by various simulations on the randomly generated DEM and obstacle map.

• 제어로봇시스템학회논문지
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• 제17권9호
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• pp.916-921
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• 2011

Mobile robot localization is the task of estimating the robot pose in a given environment. This research deals with outdoor localization based on an elevation map. Since outdoor environments are large and contain many complex objects, it is difficult to robustly estimate the robot pose. This paper proposes a Hausdorff distance-based map matching method. The Hausdorff distance is exploited to measure the similarity between extracted features obtained from the robot and elevation map. The experiments and simulations show that the proposed Hausdorff distance-based map matching is useful for robust outdoor localization using an elevation map. Also, it can be easily applied to other probabilistic approaches such as a Markov localization method.

• Journal of Advanced Marine Engineering and Technology
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• 제40권1호
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• pp.62-68
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• 2016

실내 위치인식 기술 중 하나인 WiFi Fingerprint는 기존의 WiFi access point(AP)의 거리에 따른 신호 세기를 활용하여 위치를 추정하는 편리함 때문에 많은 연구가 이루어지고 있다. 하지만 이 방식은 Radio map에 저장된 Reference point에 의존하기 때문에 다른 방식에 비해 위치의 분해능이 떨어지고 연산량이 많다. 본 논문에서는 이러한 문제를 해결하기 위하여 WiFi와 BLE를 융합한 Log-Distance Path Loss Model 기반의 Radio map 설계 알고리즘을 제안한다. 제안한 알고리즘은 Log-Distance Path Loss Model이 적용된 변수 값을 추출하여 Radio map을 설계하는 방식이며 Median Filter를 적용하여 오차를 개선하였다. 기존 Fingerprint와 비교하여 실험한 결과, 위치의 정확도는 평균 2.747m에서 2.112m로 0.635m 감소되는 것을 확인하였으며 연산량은 AP 환경에 따라 33%이상 감소하는 것을 확인하였다.

• 조명전기설비학회논문지
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• 제20권9호
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• pp.45-53
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• 2006

This paper proposes a method for an effective intelligent route decision for automatic moving robots(AMR) using a 2D spatial map of a stereo camera system. In this method, information about depth and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle is detected, and a 2D spatial map is obtained from the location coordinates. Then the relative distances between the obstacle and other objects are deduced. The robot move automatically by effective and intelligent route decision using the obtained 2D spatial map. From experiments on robot driving with 240 frames of stereo images, it was found that the error ratio of the calculated distance to the measured distance between objects was very low, 1.52[%] on average.

• International Journal of Internet, Broadcasting and Communication
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• 제8권4호
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• pp.54-57
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• 2016

In this paper, the method for an effective and intelligent route decision of the automatic ground vehicle (AGV) using a 2D spatial map of the stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle detected and the 2D spatial map obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The AGV moves automatically by effective and intelligent route decision using the obtained 2D spatial map. From some experiments on robot driving with 480 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 1.57% on average, respectably.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.101-106
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• 2019

In this paper, we investigate the patient fall prevention system to prevent the patient from falling out of the bed unintentionally on the bed of the bed. Patients stay in bed for many hours of hospitalization. During the hospitalization period, patients have low controllability of the body, as compared with normal persons, and fall due to intentional movements, resulting in a fall of the patient, can be a fatal threat to the patient. Therefore, an efficient fall prevention system is required. In this paper, the distance map to the patient is generated by the distance measuring sensor on the bed of the patient, and the risk is determined by estimating the position of the patient based on the distance map. As a result, when the distance map of the dangerous area is 150 mm or more, it is determined to be dangerous, and good results are obtained.

• 방송공학회논문지
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• 제17권6호
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• pp.933-944
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• 2012

본 논문은 저해상도의 깊이맵을 고해상도의 깊이맵으로 변환하는 새로운 방법인 거리 변환 기반의 양측 업샘플링 기법을 제안한다. 제안하는 방법은 깊이맵의 거리변환 값에 따라 공간 도메인 가중치 함수를 조절하기 때문에 에지의 선명도를 유지하면서 깊이맵의 해상도를 증가시킨다. 이를 위해, 제안하는 방법은 거리 변환 단계, 공간 가중치 조절 단계, 영상 보간 단계를 거친다. 다양한 실험 깊이 맵을 통한 실험에서 제안하는 방법이 기존의 양측 업샘플링 방법보다 출력 깊이맵의 화질 관점에서 성능이 좋아짐을 확인했다.

• Steel and Composite Structures
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• 제47권4호
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• pp.451-454
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• 2023

Landslides are one of the natural disasters that cause a lot of financial and human losses every year It will be all over the world. China, especially. The Mainland China can be divided into 12 zones, including 4 high susceptibility zones, 7 medium susceptibility zones and 1 low susceptibility zone, according to landslide proneness. Climate and physiography are always at risk of landslides. The purpose of this research is to prepare a landslide hazard map using the Hierarchical Analysis Process method. In the GIS environment, it is in a part of China watershed. In order to prepare a landslide hazard map, first with Field studies, a distribution map of landslides in the area and then a map of factors affecting landslides were prepared. In the next stage, the factors are prioritized using expert opinion and hierarchical analysis process and nine factors including height, slope, slope direction, geological units, land use, distance from Waterway, distance from the road, distance from the fault and rainfall map were selected as effective factors. Then Landslide risk zoning in the region was done using the hierarchical analysis process model. The results showed that the three factors of geological units, distance from the road and slope are the most important have had an effect on the occurrence of landslides in the region, while the two factors of fault and rainfall have the least effect The landslide occurred in the region.

• 로봇학회논문지
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• 제16권3호
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• pp.189-198
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• 2021

In this paper, we introduce the software/hardware system that can reliably calculate the distance from sensor to the model regardless of point cloud density. As the 3d point cloud map is widely adopted for SLAM and computer vision, the accuracy of point cloud map is of great importance. However, the 3D point cloud map obtained from Lidar may reveal different point cloud density depending on the choice of sensor, measurement distance and the object shape. Currently, when measuring map accuracy, high reflective bands are used to generate specific points in point cloud map where distances are measured manually. This manual process is time and labor consuming being highly affected by Lidar sparsity level. To overcome these problems, this paper presents a hardware design that leverage high intensity point from three planar surface. Furthermore, by calculating distance from sensor to the device, we verified that the automated method is much faster than the manual procedure and robust to sparsity by testing with RGB-D camera and Lidar. As will be shown, the system performance is not limited to indoor environment by progressing the experiment using Lidar sensor at outdoor environment.

• 한국CDE학회논문집
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• 제15권2호
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• pp.115-123
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• 2010

We present an efficient algorithm for computing the Hausdorff distance between two planar curves. The algorithm is based on an efficient trimming technique that eliminates the curve domains that make no contribution to the final Hausdorff distance. The input curves are first approximated with biarcs within a given error bound in a pre-processing step. Using the biarc approximation, the distance map of an input curve is then approximated and stored into the graphics hardware depth-buffer by rendering the distance maps (represented as circular cones) of the biarcs. We repeat the same procedure for the other input curve. By sampling points on each input curve and reading the distance from the other curve (stored in the hardware depth-buffer), we can easily estimate a lower bound of the Hausdorff distance. Based on the lower bound, the algorithm eliminates redundant curve segments where the exact Hausdorff distance can never be obtained. Finally, we employ a multivariate equation solver to compute the Hausdorff distance efficiently using the remaining curve segments only.