• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.35-45
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• 2013

A autonomous vehicle requires improved and robust perception systems than conventional perception systems of intelligent vehicles. In particular, single sensor based perception systems have been widely studied by using cameras and laser radar sensors which are the most representative sensors for perception by providing object information such as distance information and object features. The distance information of the laser radar sensor is used for road environment perception of road structures, vehicles, and pedestrians. The image information of the camera is used for visual recognition such as lanes, crosswalks, and traffic signs. However, single sensor based perception systems suffer from false positives and true negatives which are caused by sensor limitations and road environments. Accordingly, information fusion systems are essentially required to ensure the robustness and stability of perception systems in harsh environments. This paper describes a perception system for autonomous vehicles, which performs information fusion to recognize road environments. Particularly, vision and laser radar sensors are fused together to detect lanes, crosswalks, and obstacles. The proposed perception system was validated on various roads and environmental conditions with an autonomous vehicle.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.339-340
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• 2008

로봇의 현재 위지 추적은 무인 로봇 자동 항법시스템의 중요 기술로 센서 데이터로부터 로봇의 위치를 결정하고 환경맵을 구성하는 것이다. 기존 방법으로는 초음파, 레이저 등의 거리 측정 센서를 이용해 로봇의 전역 위치를 찾는 방법과 스테레오 비전을 통한 방법이 개발되었다. 거리 측정 센서만으로 로봇위치 추적 알고리즘은 계산량이 감소하고 비용이 적게 들지만 센서오차율 및 환경장애에 따른 오류가 크다. 이에 반해 스테레오 비전 시스템은 3차원 공간영역을 정확히 측정할 수 있지만 계산량이 많아 고사양의 시스템을 요구하고 알고리즘 구현에 어려움이 있다. 따라서 본 논문에서는 단일 카메라 영상과 PSD(position sensitive device) 센서를 사용하여 로봇의 현재 위치를 추적하고 환경맵을 구성하여 자율이동이 가능한 시스템을 제안한다.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.338-344
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• 2010

Both ends of welding line are often closed by wall in the welding of ship blocks. In this research, seam tracking sensing system for butt welding in the condition with wall was developed. Seam tracking sensing system measures position of carriage from wall and detects root-pass of welding line. The system consists of the laser displacement sensors and ultrasonic sensors. The laser displacement sensor reciprocal1y rotates by the motor and measures a distance from laser sensor to the welding material. The ultrasonic sensor measures a distance between welding system and walls. The distance measured by the ultrasonic sensor is used to get X(driving) position and to determine initial and end point of the weld line. Y(weaving) and Z(height) of the weld line are obtained by the distance measured by the laser displacement sensor and the orientation of the sensor. The sensing system includes the controller that is independent from the welding carriage. The seam tracking sensing system is attached to both side of welding carriage so that interference between welding torch and sensing system can be avoided during the welding. And both side sensing system minimize dead zone. Finally, developed sensing system was adhered to welding carriage and verified usefulness by experiments.

• Journal of Sensor Science and Technology
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• v.12 no.5
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• pp.225-230
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• 2003

Nowadays, laserthermia is widely used to treat malignant tumors with generating heat as the one of minimal invasive surgeries. Generally, the laserthermia probe system consists of the fiber-optic laser and light guides, image guide and temperature sensor. It is very important to measure the temperature of treating tumor and make a stable temperature ($42{\sim}43^{\circ}C$) during the treating time. Therefore, laserthermia probe needs temperature sensor which can measure it exactly and fast. In this study, to develop a new type of temperature sensor with LC(liquid crystal) and optical fiber, the reflectivity of LC according to the temperature changes are measured. Also, the relationships are derived from the results.

• Journal of Navigation and Port Research
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• v.30 no.10 s.116
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• pp.839-845
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• 2006

A laser docking system provides a centimeter-level accuracy distance from jetty mounted laser sensors in order to help a vessel to approach to a pier. It is very accurate & useful, whereas there are too many considerable problems. Laser sensors of the laser docking system need to be correctly positioned and installed on a jetty to allow for full range of vessels to be berthed and to consider loading condition and tidal variations. Above all, the laser docking system is expensive and its service coverage is limited. In order to solve these problems, CDGPS positioning method using GPS satellites has been proposed. This paper presents that, through RHDOP simulation, the previous CDGPS positioning method using only GPS satellites is not able to provide the continuous service with centimeter-level positioning accuracy. And this paper proposes a pseudolite-augmented positioning method for vessel docking in order to solve the problem of the continuous service on the previous CDGPS positioning method. In this paper, pseudolite is used to aid in CDGPS positioning. This paper shows that the proposed method can provides the continuous service through comparison analysis of RHDOP simulation results between the GPS satellite constellation and the pseudolite-augmented GPS satellite constellation. Furthermore, it is shown that the proposed positioning method satisfies the positioning performance required for vessel automatic docking at a test bed designed for performance evaluation.

• Journal of Animal Environmental Science
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• v.17 no.2
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• pp.93-100
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• 2011

This study was conducted to verify the applicability of robot milking system through acquisition and analysis of model teat's position information using scanning range finder (SRF). Model teats, same size and shape as real teats, were designed to analyze the properties according to the material, distance error and angle error of the sensor. In addition, 2-dimensional distance information of each teats was obtained at same time with 4 teat models and the result were as follows. 1. In the case of the fingers on the experiment for selection of materials for teat model, the distance error was from 4.3 mm to 1.3 mm, average was 2.8 mm as a minimum record. In the case of rubber material, average distance error was 4.3 mm. So, this material was considered to be a most suitable model. 2. The distance error was maximum at 100 mm distance. The more distance increased, the less error increased up to 300 mm. Then the error increased after 300 mm and decreased again. 3. The maximum angle error of 10.1 mm was measured at $170^{\circ}$, in case of $70^{\circ}$ the error was 0.2 mm as a minimum value. There was no specific tendency to error of angle. 4. In the 2-dimensional location error for 4 teat models, distance error was 3.8 mm as minimum and 7.2 mm as maximum. The angle error was $1.2^{\circ}$ as maximum. All of errors were included within the accuracy of sensor, the robot milking system was considered to be applicable to measure the distance of teats due to the measuring velocity of SRF and the hole size of teat-cup.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.132-142
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• 2014

Stereo camera is drawing attention as an essential sensor for future intelligence robot system since it has the advantage of acquiring not only distance but also other additive information for an object. However, it cannot match correlated point on target image for low textured region or periodic patterned region such as wall of building or room. In this paper, we propose a stereo matching technique that increase the matching performance by fusing belief propagation stereo matching algorithm and local distance measurements of 2D-laser range finder in order to overcome this kind of limitation. The proposed technique adds laser measurements by referring quad-tree based segment information on to the local-evidence of belief propagation stereo matching algorithm, and calculates compatibility function by reflecting over-segmented information. Experimental results of the proposed method using simulation and real test images show that the distance information for some low textured region can be acquired and the discontinuity of depth information is preserved by using segmentation information.

• Journal of Welding and Joining
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• v.17 no.2
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• pp.53-60
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• 1999

Conventionally, CCD camera and vision sensor using the projected pattern of light is generally used to inspect the weld bead defects. But with this method, a lot of time is needed for image preprocessing, stripe extraction and thinning, etc. In this study, laser vision sensor using the scanning beam of light is used to shorten the time required for image preprocessing. The software for deciding whether the weld bead is in proper shape or not in real time is developed. The criteria are based upon the classification of imperfections in metallic fusion welds(ISO 6520) and limits for imperfections(ISO 5817).

• Journal of Digital Contents Society
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• v.11 no.2
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• pp.117-122
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• 2010

This is a study on the analysis of vibration mode of a laser doppler. We measure the vibration mode of a doppler and analyze each component, and want to estimate three dimensional properties from 2-dimensional data. The vibration mode relies on a range detector that uses a distance sensor. Since the outputs are determined by the measured distance, we want to study how 3-dimensional vibration mode is generated from 2-dimensional ones. The study will include the patterns of generating a 3-dimensional vibration mode as well as the relationship between the distance and the vibration mode.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.149-156
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• 2008

SLAM(Simultaneous Localization and Mapping) system is to find a global position and build a map with sensing data when an unmanned-robot navigates an unknown environment. Two kinds of system were developed. One is used distance measurement sensors such as an ultra sonic and a laser sensor. The other is used stereo vision system. The distance measurement SLAM with sensors has low computing time and low cost, but precision of system can be somewhat worse by measurement error or non-linearity of the sensor In contrast, stereo vision system can accurately measure the 3D space area, but it needs high-end system for complex calculation and it is an expensive tool. In this paper, we implement the SLAM system using a single camera image and a PSD sensors. It detects obstacles from the front PSD sensor and then perceive size and feature of the obstacles by image processing. The probability SLAM was implemented using the data of sensor and image and we verify the performance of the system by real experiment.