• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.945-946
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• 2015

Laser Range Finder를 이용하여 생성한 3차원 점군 정보는 단면적인 부분만 볼 수 있으며, 잡음이 포함되어 작은 물체를 추출하는데 많은 영향이 생긴다. 이러한 잡음이 있는 3차원 점군 정보 사이에서 밸브의 중심의 위치에 대한 추가적인 입력을 받아 원환체, 원통, 평면의 정보를 복합적으로 포함하고 있는 밸브의 모델을 추출한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.973-979
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• 2007

A laser vision system is developed to measure the three-dimensional feature of an object. This system consists of two low cost cameras and a cross laser. One camera and a cross laser are used to measure a plane equation of an object. Using this information, the other camera measures a hole size of an object. The proposed system provides 0.05 mm accuracy measurement systems with relatively low cost.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.355-361
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• 2006

In large scale environments like airport, museum, large warehouse and department store, autonomous mobile robots will play an important role in security and surveillance tasks. Robotic security guards will give the surveyed information of large scale environments and communicate with human operator with that kind of data such as if there is an object or not and a window is open. Both for visualization of information and as human machine interface for remote control, a 3D model can give much more useful information than the typical 2D maps used in many robotic applications today. It is easier to understandable and makes user feel like being in a location of robot so that user could interact with robot more naturally in a remote circumstance and see structures such as windows and doors that cannot be seen in a 2D model. In this paper we present our simple and easy to use method to obtain a 3D textured model. For expression of reality, we need to integrate the 3D models and real scenes. Most of other cases of 3D modeling method consist of two data acquisition devices. One for getting a 3D model and another for obtaining realistic textures. In this case, the former device would be 2D laser range-finder and the latter device would be common camera. Our algorithm consists of building a measurement-based 2D metric map which is acquired by laser range-finder, texture acquisition/stitching and texture-mapping to corresponding 3D model. The algorithm is implemented with laser sensor for obtaining 2D/3D metric map and two cameras for gathering texture. Our geometric 3D model consists of planes that model the floor and walls. The geometry of the planes is extracted from the 2D metric map data. Textures for the floor and walls are generated from the images captured by two 1394 cameras which have wide Field of View angle. Image stitching and image cutting process is used to generate textured images for corresponding with a 3D model. The algorithm is applied to 2 cases which are corridor and space that has the four wall like room of building. The generated 3D map model of indoor environment is shown with VRML format and can be viewed in a web browser with a VRML plug-in. The proposed algorithm can be applied to 3D model-based remote surveillance system through WWW.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.26-34
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• 2008

The information of traversability and path planning is essential for UGV(Unmanned Ground Vehicle) navigation. Such information can be obtained by analyzing 3D terrain. In this paper, we present the method of 3D terrain modeling with color information from a camera, precise distance information from a 2D Laser Range Finder(LRF) and wheel encoder information from mobile robot with less data. And also we present the method of 3B terrain modeling with the information from GPS/IMU and 2D LRF with less data. To fuse the color information from camera and distance information from 2D LRF, we obtain extrinsic parameters between a camera and LRF using planar pattern. We set up such a fused system on a mobile robot and make an experiment on indoor environment. And we make an experiment on outdoor environment to reconstruction 3D terrain with 2D LRF and GPS/IMU(Inertial Measurement Unit). The obtained 3D terrain model is based on points and requires large amount of data. To reduce the amount of data, we use cubic grid-based model instead of point-based model.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.145-148
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• 2000

Nowadays there are lots of researches on robot systems working on danger environments and control led remotely. In this paper, we describe a virtual robot interface system based on Internet In the system, a client can order scanning for range finding, then server detects a 3D profile data from the objects by using robot controlling and a range finder automatically. If one clicks the original position of object and destination on virtual space, the robot moves the object to the new position in real space. The proposed interface system supports advanced virtual 3D interface and makes it possible one to manage the objects remotely more conveniently.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.22 no.1
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• pp.6-10
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• 1986

The feasibility of passive detection of fishes which had been caught in the fishing grounds near the Korean peninsula was theoretically investigated. Considering the commercial importance and the acoustical informations readily identified, although many species of fish make noise, Croaker is clarified to be a representative fish for passive fish detection. Assuming a source level of the sound produced by croakers is given as 150-18OdB (re 1l'pa, 500 Hz bandwidth), The range detected by a passive line array sonar is estimated to be about 3-20km. In addition, the tonal noise (700~800Hz) made by croaker that is easily separated from underwater noise is expected to increase the ability to discriminate from the other species of fish.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.243-250
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• 2012

This paper proposes a 3D map-building algorithm using one LRF (Laser Range Finder) while a mobile robot is navigating on the slanted surface. There are several researches on 3D map buildings using the LRF. However most of them are performing the map building only on the flat surface. While a mobile robot is moving on the slanted surface, the view angle of LRF is dynamically changing, which makes it very difficult to build the 3D map using encoder data. To cope with this dynamic change of the view angle in build 3D map, IMU and balance filters are fused to correct the unstable encoder data in this research. Through the real navigation experiments, it is verified that the fusion of multiple sensors are properly performed to correct the slope angle of the slanted surface. The effectiveness of the balance filter are also checked through the hill climbing navigations.

• The Journal of Korea Robotics Society
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• v.3 no.1
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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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.417-418
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• 2012

본 논문에서는 3차원 데이터를 이용한 효율적인 실내 공간 표현 기법을 제안한다. 제안하는 기법은 3차원 데이터의 획득과 실내 구조 및 영상 정보를 표현하기 위한 표현 복원으로 구성된다. 3차원 데이터는 레이저 거리 측정기(laser range finder, LRF)와 전방향(omni) 카메라를 통해 획득한 포인트 클라우드 공간 정보와 전방향 텍스쳐 영상으로 구성된다. 실내 구조를 복원하기 위해, 획득한 포인트 클라우드를 복셀 격자 기반의 샘플링 기법을 통해 균일화하고 포아송 표면 재구성(Poisson surface rocoostruction) 기법을 통해 3차원 메쉬를 생성한다. 그리고 전방향 텍스쳐 영상과 3차원 메쉬외 기하학적 관계를 이용한 텍스쳐 매핑 기법을 통해 최종적으로 3차원 메쉬 표면을 복원한다. 실험 결과를 통해 제안하는 기법이 실내 공간을 효과적으로 표현함을 확인한다.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.315-327
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• 2017

In this paper, we present a method for estimating of position and velocity of a moving target by using the range and the bearing measurements from multiple sensors of aiming unit. In many cases, conventional low cost gyro sensor and a portable laser range finder(LRF) degrade the accuracy of estimation. To enhance these problems, we propose two methods. The first is background image tracking and the other is principal component analysis (PCA). The background tracking is used to assist the low cost gyro censor. And the PCA is used to cope with the problems of a portable LRF. In this paper, we prove that our method is robust with respect to low-frequency, biased and noisy inputs. We also present a comparison between our method and the extended Kalman filter(EKF).