• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1246-1253
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• 2009

To be high efficient for a navigation of unmanned ground vehicle, it must be able to distinguish between safe and hazardous regions in its immediate environment. We present an advanced method using laser range finder for building global 2D digital maps that include environment information. Laser range finder is used for mapping of obstacles and driving environment in the 2D laser plane. Rotary encoders are used for localization of UGV. The main contributions of this research are the development of an algorithm for global 2D map building and it will turn a UGV navigation based on map matching into a possibility. In this paper, a map building algorithm will be introduced and an assessment of algorithm reliability is judged at an each environment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.180-180
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• 2004

정밀한 계측의 필요성이 높아지면서 레이저는 그 신뢰성과 사용 편의성으로 인해 거리측정에도 높은 활용을 보이고 있다. 레이저 거리측정기(laser range finder, LRF)의 원리는 20ns 미만의 짧은 레이저 펄스를 표적에 발사한 후 반사되어 돌아오는 신호의 시간과 빛의 속도를 곱하여 거리를 계산하는 방식이다. 이러한 반사펄스(pulse-echo techniques)법은 수m-수백만 km까지의 거리측정에 사용되는 방식으로서 정밀하고 빠른 측정이 가능할 뿐 아니라 단지 목표물을 확인하고 측정버튼을 누름으로써 결과를 얻을 수 있는 사용 편의성을 장점으로 한다.(중략)

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.317-318
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• 2007

One of the important factors of the autonomous mobile robot is to build a map for surround environment and estimate its localization. This paper suggests a sensor fusion method of laser range finder and monocular vision sensor for the simultaneous localization and map building. The robot observes the comer points in the environment as features using the laser range finder, and extracts the SIFT algorithm with the monocular vision sensor. We verify the improved localization performance of the mobile robot from the experiment.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.399-404
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• 1996

We developed a non-contact shape measuring device using computer image processing technology. We present a method of calibrating a CCD video camera and a laser range finder which is the most important step toward making an accurate shape measuring system. An artificial neural network is used for the calibration. Our measurement system is composed of a semiconductor laser. a CCD video camera, a personal computer, and a linear motion table. We think that the developed system could be used for measuring the change in shape of the spent nuclear fuel rod before and after irradiation which is one of the most important tasks for developing a better nuclear fuel. A radiation shield is suggested for the possible utilization of the range finder in radioactive environment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.321-322
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.659-660
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• 2008

• 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 Advanced Navigation Technology
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• v.18 no.2
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• pp.134-141
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• 2014

Mobile robots use various sensors for navigation such as wheel encoder, vision sensor, sonar, and laser sensors. Dead reckoning is used with wheel encoder, resulting in the accumulation of positioning errors. For that reason wheel encoder can not be used alone. Too much information of vision sensors leads to an increase in the number of features and complexity of perception scheme. Also Sonar sensor is not suitable for positioning because of its poor accuracy. On the other hand, laser sensor provides accurate distance information relatively. In this paper we propose to extract the angular information from the distance information of laser range finder and use the Kalman filter that match the heading and distance of the laser range finder and those of wheel encoder. For laser scanner with one feature point error may increase much when the feature point is variant or jumping to a new feature point. To solve the problem, we propose to use two feature points and show that the positioning error can be reduced much.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.4
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• pp.177-186
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• 2015

For data fusion of laser range finder (LRF) and vision camera, accurate calibration of external parameters which describe relative pose between two sensors is necessary. This paper proposes a new calibration method which can acquires more accurate external parameters between a LRF and a vision camera compared to other existing methods. The main motivation of the proposed method is that any corner data of a known 3D structure which is acquired by the LRF should be projected on a straight line in the camera image. To satisfy such constraint, we propose a 3D geometric model and a numerical solution to minimize the energy function of the model. In addition, we describe the implementation steps of the data acquisition of LRF and camera images which are necessary in accurate calibration results. In the experiment results, it is shown that the performance of the proposed method are better in terms of accuracy compared to other conventional methods.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.591-597
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• 1996

To straighten the path that farm machinery follows in paddy fields, it is necessary to measure and evaluate the tracks that these machines leave behind. However, there are no known methods for making such measurements and evaluations since it is difficult to accurately trace the paths that the machine make in paddy fields. Therefore, a measuring system has been developed which can accurately recored the path of a farm machinery in a field by measuring the horizontal straight-line distance from the side of the field to the machine. This system consists of a track subsystem on the machine and a range finder system. A measuring appraratus is installed on a flatcar which runs on rails over 50 m long at the side of the filed. The track subsystem uses a CCD camera to track the movement of the machine in the field which is following a lengthwise path. The range finder subsystem measures the distance that the measuring apparatus has traveled on the rails and the distance from the app ratus to the machine in the field. This system makes it possible to record the path that the machine travels. Even though differences in traveling distance arise between the measuring apparatus and the farm machine, these differences are detected by image processing , which allows the machine in the field to be located accurately. The short(0.05 second) time required for image processing is enough to follow an object . In the present study, this system was able to measure the path that a moving tractor makes. Even though a lag of up to 0.4 meters occurred, this system did not miss its target during operation of the track subsystem. Thus the path measuring system developed here is able to record vehicle paths automatically by following the movement of vehicles in the field and measuring the distance to them. It is expected to come into use in such applications as unmanned moving vehicle tests.