• 로봇학회논문지
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• 제19권1호
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• pp.23-30
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• 2024

This paper studies a GPS error filtering method that takes into account the continuity of the ongoing path to enhance the safety of autonomous agricultural mobile robots. Real-Time Kinematic Global Positioning System (RTK-GPS) is increasingly utilized for robot position evaluation in outdoor environments due to its significantly higher reliability compared to conventional GPS systems. However, in orchard environments, the robot's current position obtained from RTK-GPS information can become unstable due to unknown disturbances like orchard canopies. This problem can potentially lead to navigation errors and path deviations during the robot's movement. These issues can be resolved by filtering out GPS information that deviates from the continuity of the waypoints traversed, based on the robot's assessment of its current path. The contributions of this paper is as follows. 1) The method based on the previous waypoints of the traveled path to determine the current position and trajectory. 2) GPS filtering method based on deviations from the determined path. 3) Finally, verification of the navigation errors between the method applying the error filter and the method not applying the error filter.

• 방송공학회논문지
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• 제22권4호
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• pp.496-508
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• 2017

본 논문은 전역적 대비를 보존하는 동시에 경계 정보를 정확히 보존할 수 있는 혼합 톤 매핑 기법 (Tone Mapping Operator: TMO)을 제안한다. 우선, 넓은 동적 영역 (High Dynamic Rangae: HDR) 영상을 낮은 동적 영역 (Low Dynamic Range: LDR) 디스플레이에 적합하게 압축하기 위해 인간의 시각 시스템 (Human Visual System: HVS)에 기반한 임계 값 대 밝기 값 (Threshold vs. Intensity: TVI) 함수와 영상의 대비를 사용하였으며 이에 따라 영상의 전역적인 대비를 보존할 수 있었다. 또한, 가이디드 영상 필터링 (Guided Image Filtering: GIF)을 이용하여 검출된 경계 정보와 변화감지역 (Just Noticeable Difference: JND) 모델의 공간적 마스킹을 이용하여 검출된 경계 정보를 결합함으로써 영상의 경계를 보존하고 출력 영상의 인지적 화질을 향상시켰다. 기존에 TMO들은 크게 전역적 톤 매핑 (Global Tone Mapping: GTM)과 지역적 톤 매핑 (Local Tone Mapping: LTM)으로 분류되었다. GTM은 전역적인 대비를 보존하며 구현이 단순해 실행시간이 빠르다는 장점이 있지만 영상의 경계 정보가 손실되며 지역적 대비를 보존하지 못하는 단점이 있었다. 반면 LTM은 영상의 지역적 대비와 경계 정보를 잘 보존하였지만 경계 영역에서의 헤일로 열화 현상의 발생과 같이 일부 영역이 부자연스럽게 표현되는 경우가 발생하였으며 GTM과 비교하여 높은 계산 복잡도를 가졌다. 따라서 본 논문에서는 GTM과 LTM의 장점을 결합하여 전역적인 대비를 보존하는 동시에 영상의 경계 정보를 보존하는 TMO를 제안하였으며 실험결과를 통해 제안하는 톤 매핑 기법이 인지적 화질 측면에서 성능이 우수한 것으로 확인되었다.

• 한국멀티미디어학회논문지
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• 제18권6호
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• pp.691-700
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• 2015

Here, we present a new framework for histogram equalization in which both local and global contrasts are enhanced using neighborhood metrics. When checking neighborhood information, filters can simultaneously improve image quality. Filters are chosen depending on image properties, such as noise removal and smoothing. Our experimental results confirmed that this does not increase the computational cost because the filtering process is done by our proposed arrangement of making the histogram while checking neighborhood metrics simultaneously. If the two methods, i.e., histogram equalization and filtering, are performed sequentially, the first method uses the original image data and next method uses the data altered by the first. With combined histogram equalization and filtering, the original data can be used for both methods. The proposed method is fully automated and any spatial neighborhood filter type and size can be used. Our experiments confirmed that the proposed method is more effective than other similar techniques reported previously.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.930-932
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• 2003

For this study we used a CCD video camera to capture the pavement image information via the computer. During investigation processing, the CCD video camera captured 10${\sim}$30 images per second. If the vehicle velocity is too fast, the collected images will be duplicated and if the velocity is too slow there will be a gapped between images. Therefore, in order to control the efficiency of the image grabber we should add accessory tools such as the Differential Global Positioning System (DGPS) and odometer. Furthermore, Kalman Filtering can also solve these problems. After the CCD video camera captured the pavement images, we used the Least-Squares method to eliminate images of gradation which have non-uniform surfaces due to the illumination at night. The Fuzzy Entropy method calculates images of threshold segments and creates binary images. Finally, the Object Labeling algorithm finds objects that are cracks or noises from the binary image based on volume pixels of the object. We used these algorithms and tested them, also providing some discussion and suggestions.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.101.4-101
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• 2001

Evolutionary algorithm has been receiving a remarkable attention due to the model-free and population-based parallel search attributes and much successful results are coming out. However, there are some problems in most of the evolutionary algorithms. The critical one is that it takes much time or large generations to search the global optimum in case of the objective function with multimodality. Another problem is that it usually cannot search all the local optima because it pays great attention to the search of the global optimum. In addition, if the objective function has several global optima, it may be very difficult to search all the global optima due to the global characteristics of the selection methods. To cope with these problems, at first we propose a preprocessing process, grid-filtering algorithm(GFA), and propose a new distributed evolutionary ...

• 로봇학회논문지
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• 제3권1호
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.737-753
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• 2021

As the demand for high-quality rendering for mixed reality, videogame, and simulation has increased, global illumination has been actively researched. Monte Carlo path tracing can realize global illumination and produce photorealistic scenes that include critical effects such as color bleeding, caustics, multiple light, and shadows. If the sampling rate is insufficient, however, the rendered results have a large amount of noise. The most successful approach to eliminating or reducing Monte Carlo noise uses a feature-based filter. It exploits the scene characteristics such as a position within a world coordinate and a shading normal. In general, the techniques are based on the denoised pixel or sample and are computationally expensive. However, the main challenge for all of them is to find the appropriate weights for every feature while preserving the details of the scene. In this paper, we compare the recent algorithms for removing Monte Carlo noise in terms of their performance and quality. We also describe their advantages and disadvantages. As far as we know, this study is the first in the world to compare the artificial intelligence-based denoising methods for Monte Carlo rendering.

• 전기전자학회논문지
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• 제19권2호
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• pp.244-253
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• 2015

본 논문은 비의도 움직임 검출 및 적응적 움직임 완화 필터를 이용한 동영상 안정화 기법을 제안한다. 제안된 기법은 비의도 움직임 검출 단계와 검출된 비의도 움직임을 완화 필터링하는 단계로 구성된다. 움직임 완화 과정에 요구되는 속성들을 활용하기 위하여 누적 전역 움직임 매개변수들로 구성된 집합의 국부 최대값과 국부 최소값을 정의한다. 국부 정보를 사용하여 비의도 움직임 검출에 필요한 제약조건을 정의하며, 제약조건들을 기반으로 하여 알파-조정 평균 필터의 알파 값을 결정하여 재구성된 동영상의 움직임 완화 정도를 제어한다. 실험 결과를 통해 제안된 방식의 성능 우수성을 입증하였다.

• Smart Structures and Systems
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• 제11권4호
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• pp.331-348
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• 2013

Effective monitoring, reliable data analysis, and rational data interpretations are challenges for engineers who are specialized in bridge health monitoring. This paper demonstrates how to use the Global Positioning System (GPS) and accelerometer data to accurately extract static and quasi-static displacements of the bridge induced by ambient effects. To eliminate the disadvantages of the two separate units, based on the characteristics of the bias terms derived from the GPS and accelerometer respectively, a wavelet based multi-step filtering method by combining the merits of the continuous wavelet transform (CWT) with the discrete stationary wavelet transform (SWT) is proposed so as to address the GPS deformation monitoring application more efficiently. The field measurements are carried out on an existing suspension bridge under the normal operation without any traffic interference. Experimental results showed that the frequencies and absolute displacements of the bridge can be accurate extracted by the proposed method. The integration of GPS and accelerometer can be used as a reliable tool to characterize the dynamic behavior of large structures such as suspension bridges undergoing environmental loads.

• 한국시뮬레이션학회논문지
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• 제16권4호
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• pp.57-65
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• 2007

많은 센서 네트워크 응용에서, 센서 노드들은 개방된 환경에 배포되므로 노드의 암호 키 완전히 훼손하는 물리 공격에 취약하다. 위조 감지 보고서는 훼손된 노드를 통하여 네트워크에 주입될 수 있으며, 이는 거짓 경보를 울릴 수 있을 뿐만 아니라 전지로 동작하는 네트워크의 제한된 에너지 자원을 고갈시킬 수 있다. Fan Ye 등은 이에 대한 대안으로 전송과정에서 허위 보고서를 검증할 수 있는 통계적 여과 기법을 제안하였다. 이 기법에서 허위 보고서에 대한 검증이 가능한 인증키의 노출 정도인 훼손 허용도를 나타내는 분할 값은 전역 키 풀이 나눠진 구획들의 수로 소비 에너지와 서로 대치되는 관계에 있어 그 결정이 매우 중요하다. 전체 구획들의 인증키가 노출될 경우 허위 보고서를 더 이상 검증을 할 수 없고 각 구획들의 노출되지 않은 나머지 인증키들은 인증키로써의 기능도 잃게 된다. 본 논문에서는 전역 키 풀 분할에 퍼지 규칙 시스템을 사용해 다수의 구획들로 나누는 퍼지 기반의 적응형 분할 기법을 제안한다. 퍼지 로직은 훼손된 구획의 수, 노드의 밀도와 잔여 에너지양을 고려하여 분할 값을 결정한다. 이 퍼지 기반의 분할 값은 충분한 훼손 허용도를 제공하면서 에너지를 보존할 수 있다.