• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.170-170
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• 2012

정보통신 기술 발전과 함께 자동차 및 로봇 산업에서도 다양한 IT 기술이 적용되고 있다. 지능형 로봇 및 자율 주행 자동차의 실현을 위해서는 필수적인 센서 기술이 수반되어야 한다. 자동차 및 로봇 산업에서 종래의 센서와 더불어 레이저를 이용한 센서 기술 적용으로 보다 업그레이드 된 성능을 갖게 되었다. 특히, 반도체 레이저를 이용한 전방 물체 및 거리 인식 센서를 사용함으로써 보다 정밀한 분해능과 장거리의 거리 계측이 가능하게 되었다. RF나 초음파 센서보다 우수한 성능을 가진 반도체 레이저 거리 계측 센서를 위한 박막 성장과 성장된 Wafer의 칩 프로세스 공정을 진행하여 레이저 센서로 적용 가능함을 확인하였다. InP 기판 위해 클래드, 도파로, 활성층을 MOCVD 장비로 각각 성장하였으며, 도파로는 비대칭 구조로 성장이 되었다.

• 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 Vacuum Society Conference
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• 2014.02a
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• pp.332.1-332.1
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• 2014

정보통신 기술의 발전으로 지능형 자동차와 같은 미래형 고부가 가치 자동차 산업은 지속적인 성장이 기대된다. 그리고, 안전과 직결되는 차간 거리 계측은 다양한 종류의 센서에 의해 측정이 되고 있으며, 운전자 및 탑승자의 생명을 보호하고 있다. 다양한 차간 거리센서 중에서도 전방의 물체 인식 및 넓은 영역, 장거리에 대한 센싱은 레이저를 이용하여 구현할 수 있다. 본 논문은 자동차 뿐만 아니라, 지능형 자율 주행시 전방의 물체 인식 및 거리 계측 센서로 적용이 가능한 반도체 레이저의 설계 및 제작에 관해 소개한다. 반도체 레이저는 물질에 따라 각각 다른 파장대역의 광을 조사하고 있으며 이 레이저 빔은 물체에 맞고 부딪히면 반사되어 되돌아 오는 특성을 가지고 있다. 따라서, 펄스 구동에 의해 단위 펄스당 출사되는 레이저는 전방 물체에 부딪혀 되돌아 오는 시간을 구하게 되면 레이저 광원에서 물체까지의 거리를 구할 수가 있게 된다. 여기서 펄스 레이저의 출력은 물체 감지가 가능한 거리의 정보를 가지고 있으며, 펄스로 구동될 때 반복 주파수 및 펄스 폭은 각각 거리계측 시간과 분해능을 결정하는 주요 요소가 된다. 따라서, 장거리 물체의 계측과 물체 식별 능력을 높이기 위해서는 반도체 레이저의 출력을 높이고 펄스폭을 줄여서 분해능을 향상하는 것이 필요하다. 또한, 물체 인식 또는 계측 시간을 빠르게 하기 위해서는 고속 주파수로 동작하게 되면 가능해 질 것이다. 본 논문은 1,550 nm 대역의 반도체 레이저를 제작하여 펄스 구동으로 출력과 펄스폭을 측정하였다. 또한, 보다 높은 전류에서 칩 단면의 열화를 방지하기 위한 기술을 적용하여 설계 및 제작된 레이저의 특성을 측정하여 향후, 지능형 자동차의 레이저 레이다(LIDAR)와 같은 응용분야에 많이 활용될 수 있을 것으로 기대한다.

• Korean Journal of Optics and Photonics
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• v.32 no.2
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• pp.79-85
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• 2021

In this paper, a study is conducted on the design of an optical system of a time-of-flight (TOF) laser distance sensor that can measure long distances by minimizing beam divergence. When measuring a long distance, the amount of light on the object's surface decreases as the distance increases, due to the diffusion angle of the laser beam, and thus the beam at the sensor also decreases, causing measurement errors. In general, a cylindrical lens is used to reduce the divergence beam angle. However, an optical system using a cylindrical lens has the problem of degraded performance due to the difficulty with assembly tolerance, as well as the problem of the increased size of the optical system, and thus the use of aspherical lenses has been increasing recently. Therefore, in this study, the optical efficiencies and assembly tolerances of optical systems using respectively a cylindrical lens and an aspherical lens are compared and analyzed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.101-104
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• 2011

본 논문에서는 레이저 센서를 장착한 자율 이동 로봇을 이용하여 실내에서 장애물들을 검출한다. 데이터에서 나오는 패턴을 인식해 사람과 정적 장애물을 실시간으로 구분한 후 사람의 속도와 로봇의 속도를 각각 비교하여 따로 지정해준 안전거리를 유지하며 주행한다. 예상치 못한 상황이 발생될 것을 대비해 로봇의 전방에 범퍼 센서를 장착하여 안전성을 고려하였다. 로봇의 자기 위치 인식을 위해 StarGazer센서를 이용하였다. 패턴은 레이저 센서 데이터의 거리, 각 값을 이용하여 다리 패턴의 너비를 구하고 너비의 가운데 점을 중심점으로 지정해 추적하며 구동하는 알고리즘을 구현하였다.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.5
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• pp.422-428
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• 2013

Recently, many unmanned aerial vehicle (UAV) studies have focused on small UAVs, because they are cost effective and suitable in dangerous indoor environments where human entry is limited. Map building through distance measurement is a key technology for the autonomous flight of small UAVs. In many researches for unmanned systems, distance could be measured by using laser range finders or stereo vision sensors. Even though a laser range finder provides accurate distance measurements, it has a disadvantage of high cost. Calculating the distance using a stereo vision sensor is straightforward. However, the sensor is large and heavy, which is not suitable for small UAVs with limited payload. This paper suggests a low-cost distance measurement system using a laser pointer and a monocular vision sensor. A method to measure distance using the suggested system is explained and some experiments on map building are conducted with these distance measurements. The experimental results are compared to the actual data and the reliability of the suggested system is verified.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.669-676
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• 2023

In this paper, a multi-purpose golf putting range finder based on an IR razer sensor and an inertial sensor was designed and made. It was designed to measure distance and slope within a 50m outdoor measurement range for the main purpose of golf putting distance measurement, and at the same time, it is designed to measure temperature information that affects putting. In addition, the distance meter supports house maintenance work by providing length and horizontality measurement values within the indoor 80m measurement range, and provides safety from indoor or vehicle fires by providing indoor temperature measurement values to mobile phones through linkage with the web server. In order to evaluate the accuracy of the proposed method and its interworking performance with a smartphone, a prototype was produced and a web server was built, and the usefulness was confirmed by showing an acceptable error rate within 5% in repeated experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.111-116
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• 2014

Using only laser range finder to detect the obstacles in an environment that contains transparent obstacles can not guarantee autonomous mobile robot from collision problem. To solve this problem, a mobile robot using laser range finder must be used additional sensor device such as sonar sensor that can detect the transparent obstacle. In this paper, a method is addressed to deal with the problem to detect the transparent obstacles within environment only by using laser range finder for mobile robot. In case the recognized transparent obstacle, the proposed algorithm is to localize the transparent obstacle to extract and process the reflected noise. This algorithm ensures autonomous of mobile robot only using laser range finder. The effectiveness of the proposed algorithm is evaluated by the real mobile robot and real laser range finder experiments with three case studies.