• 로봇학회논문지
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• 제1권2호
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• pp.117-124
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• 2006

In this paper, we develope the navigation system for patrol robots in indoor environment. The proposed system consists of PDA map modelling, a localization algorithm based on a global position sensor and an automatic charging station. For the practical use in security system, the PDA is used to build object map on the given indoor map. And the builded map is downloaded to the mobile robot and used in path planning. The global path planning is performed with a localization sensor and the downloaded map. As a main controller, we use PXA270 based hardware platform in which embedded linux 2.6 is developed. Data handling for various sensors and the localization algorithm are performed in the linux platform. Also, we implemented a local path planning algorithm for object avoidance with ultra sonar sensors. Finally, for the automatic charging, we use an infrared ray system and develop a docking algorithm. The navigation system is experimented with the two-wheeled mobile robot using North-Star localization system.

• 제어로봇시스템학회논문지
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• 제16권3호
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• pp.239-244
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• 2010

This paper is to present map building of mobile robot using RFID (Radio Frequency Identification) technology and ultrasonic sensor. For mobile robot to perform map building, the mobile robot needs its localization and accurate driving in space. In this reason, firstly, kinematic modeling of mobile robot under non-holonomic constrains is introduced. Secondly, based on this modeling, a tracking controller is designed for tracking a given path based on backstepping method using Lyapunov function. The Lyapunov function is also introduced for proving the stability of the designed tracking controller. Thirdly, 2D map building is performed by RFID system, mobile robot system and ultrasonic sensors. The RFID mobile robot system is composed of DC motor, encoder, ultra sonic sensor, digital compass, RFID receiver and RFID antenna. Finally, the path tracking simulation results and map building experimental results are presented to show the effectiveness of the designed controller.

• 한국정보처리학회논문지
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• 제7권2호
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• pp.558-568
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• 2000

본 논문에서는 등고선 지도의 3차원 정보를 이용하여 수치지형도 자동 생성방법을 제안한다. 제안된 방법은 등고선의 세선화와 라벨링을 통해 등고성분과 비 등고성분을 정확히 구분하였으며, Bezier 곡선을 사용하여 끊어진 등고선을 부드럽게 연결한다. 마지막으로 등고선으로부터 얻어진 고도 데이터를 사용하여 3차원 데이터를 생성한다. 제안된 방법은 수치 지형도를 만들기 위해 소요되는 막대한 양의 인력과 시간, 비용을 절약할 수 있다.

• 로봇학회논문지
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• 제19권1호
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• pp.16-22
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• 2024

Robotic grasping in unstructured environments poses a significant challenge, demanding precise estimation of gripping positions for diverse and unknown objects. Generative Grasping Convolution Neural Network (GG-CNN) can estimate the position and direction that can be gripped by a robot gripper for an unknown object based on a three-dimensional depth map. Since GG-CNN uses only a depth map as an input, the precision of the depth map is the most critical factor affecting the result. To address the challenge of depth map precision, we integrate the Segment Anything Model renowned for its robust zero-shot performance across various segmentation tasks. We adjust the components corresponding to the segmented areas in the depth map aligned through external calibration. The proposed method was validated on the Cornell dataset and SurgicalKit dataset. Quantitative analysis compared to existing methods showed a 49.8% improvement with the dataset including surgical instruments. The results highlight the practical importance of our approach, especially in scenarios involving thin and metallic objects.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.38.4-38
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• 2002

We propose a fast map-matching algorithm based on the length and the slope for the sequence of lines extracted from a laser range finder and a map. After finding two feature set from laser data and a map, the position and heading of the mobile robot can be determined exactly.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.223-230
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• 2003

Feature-based similarity retrieval has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects (e 'g', documents, images, video, music score, etc.). For example, images are represented by their color histograms, texture vectors, and shape descriptors, and are usually high-dimensional data. The performance of conventional multidimensional data structures(e'g', R- Tree family, K-D-B tree, grid file, TV-tree) tends to deteriorate as the number of dimensions of feature vectors increases. The R＊-tree is the most successful variant of the R-tree. In this paper, we propose a SOM-based R＊-tree as a new indexing method for high-dimensional feature vectors.The SOM-based R＊-tree combines SOM and R＊-tree to achieve search performance more scalable to high dimensionalities. Self-Organizing Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two dimensional space. The mapping preserves the topology of the feature vectors. The map is called a topological of the feature map, and preserves the mutual relationship (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. A best-matching-image-list. (BMIL) holds similar images that are closest to each codebook vector. In a topological feature map, there are empty nodes in which no image is classified. When we build an R＊-tree, we use codebook vectors of topological feature map which eliminates the empty nodes that cause unnecessary disk access and degrade retrieval performance. We experimentally compare the retrieval time cost of a SOM-based R＊-tree with that of an SOM and an R＊-tree using color feature vectors extracted from 40, 000 images. The result show that the SOM-based R＊-tree outperforms both the SOM and R＊-tree due to the reduction of the number of nodes required to build R＊-tree and retrieval time cost.

• 한국멀티미디어학회논문지
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• 제12권2호
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• pp.300-312
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• 2009

옥내 위치 기반 서비스를 실현하려면 옥내 측위 문제가 해결되어야 한다. 경제적으로 구현이 용이한 옥내 측위 시스템은 비교적 오차가 크다. 본 논문은 지도 정보를 반영한 옥내 측위 시스템용 보정 방법을 제안한다. 제안하는 방법은 지도 정보를 이용하여 구한 적당한 인수 값을 사용하는 칼만 필터를 이용하여 이동 객체의 궤적을 구하고, 프레쉐 거리를 이용한 지도 정합을 수행한 다음, 실시간 보정 방법을 적용한다. 제안하는 방법의 효율성을 보이는 실험 결과로 제공한다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문초록집
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• pp.382.1-382
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• 2002

This paper presents a new approach integrated Case-Based Reasoning with Self- Organization Map(SOM) in diagnosis systems. The causes of faults are obtained by case-base trained from SOM. When the vibration problem of rotating machinery occurs, this provides an exact diagnosis method that shows the fault cause of vibration problem. In order to verify the performance of algorithm, we applied it to diagnose the fault cause of the electric motor.

• ETRI Journal
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• 제34권5호
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• pp.783-786
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• 2012

This letter proposes a more advanced joint maximum a posteriori (MAP) adaptation using a prior model based on a probabilistic scheme utilizing the bilinear transformation (BIT) concept. The proposed method not only has scalable parameters but is also based on a single prior distribution without the heuristic parameters of the previous joint BIT-MAP method. Experiment results, irrespective of the amount of adaptation data, show that the proposed method leads to a consistent improvement over the previous method.

• 한국멀티미디어학회논문지
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• 제6권7호
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• pp.1286-1301
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• 2003

본 논문은 현실감 여는 실시간 영상 기반 환경 탐색을 위해 영상 분할 기반 환경 모델링에 의한 시점 변경이 가능한 환경 탐색, 다중 환경 맵을 이용한 환경 모델의 통합 및 확장에 의한 환경 탐색 방법들을 제안한다. 영상 분할 환경 모델링 방법은 환경 맵에 적용하기 용이하며 환경의 특성에 따른 깊이값 추출 방법으로 손쉽게 환경 모델링이 가능하다. 또한, 시점이 이동되고 시차를 갖는 환경의 표현이 가능하다. 그러나, 환경 맵의 단일 해상도에 의해 발생하는 영상의 흐림 현상과 가리움에 의해 환경 맵에서 없는 정보가 나타날시 발생하는 구성된 3차원 환경 모델의 늘어짐 현상이나 정보의 부족으로 인한 영상의 구멍이 발생한다. 이러한 문제를 제거하기 위해서는 다중 환경맵에 바탕을 둔 3차원 환경 모델의 재구성이 필요하다. 본 연구에서는 세밀한 환경 모델링을 통한 시차 표현과 주변 환경의 자유로운 확장을 위해 대응선 기반 환경 모델 통합 방법을 사용한다. 다중 환경맵에 의한 환경 모델링 방법은 최적의 해상도를 갖는 상세한 환경 모델을 생성할 수가 있어 시점이 자유로운 고화질의 탐색 영상 생성이 가능하다.