• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.10
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• pp.949-957
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• 2017

A laser-vision-based height measurement system is developed and implemented for the inspection of two-step variable valve lift module assemblies. The proposed laser-vision sensor module is designed based on the principle of laser triangulation. This paper summarizes the work on 3D point cloud data collection and height difference measurements. The configuration of the measurement system and the proposed height measurement algorithm are described and analyzed in detail. Additional measurement experiments on the height differences of valves and lash adjusters of a two-step variable valve lift module were implemented repeatedly to evaluate the accuracy and repeatability of the proposed measurement system. Experimental results show that the proposed laser-vision-based height measurement system achieves high accuracy, repeatability, and stabilization for the inspection of two-step variable valve lift module assemblies.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.965-971
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• 2015

This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.

• International Journal of Highway Engineering
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• v.15 no.1
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• pp.155-161
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• 2013

PURPOSES: This study is to develop a road traffic sign recognition and automatic positioning for road facility management. METHODS: In this study, we installed the GPS, IMU, DMI, camera, laser sensor on the van and surveyed the car position, fore-sight image, point cloud of traffic signs. To insert automatic position of traffic sign, the automatic traffic sign recognition S/W developed and it can log the traffic sign type and approximate position, this study suggests a methodology to transform the laser point-cloud to the map coordinate system with the 3D axis rotation algorithm. RESULTS: Result show that on a clear day, traffic sign recognition ratio is 92.98%, and on cloudy day recognition ratio is 80.58%. To insert exact traffic sign position. This study examined the point difference with the road surveying results. The result RMSE is 0.227m and average is 1.51m which is the GPS positioning error. Including these error we can insert the traffic sign position within 1.51m CONCLUSIONS: As a result of this study, we can automatically survey the traffic sign type, position data of the traffic sign position error and analysis the road safety, speed limit consistency, which can be used in traffic sign DB.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.135-141
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• 2005

Measurement of five DOF motion errors in a ultra precision feed table was attempted in this study. Yaw and pitch error were measured by using a laser interferometer and roll error was measured by using the reversal method. Linear motion errors in the vertical and horizontal directions were measured by using the sequential two point method. In this case, influence of angular motion errors was compensated by using the previously measured ones by the laser interferometer and the reversal method. The capacitive type sensors and an optical straight edge were used in the reversal method and the sequential two point method. Influence of thermal deformation on sensor jig was investgated and minimized by the periodic measurement according to the variation of room temperature. Deviation of gain between sensors was also compensated using the step response data. 5 DOF motion errors of a hydrostatic table driven by the linear motor werer tested using the measurement method. In the horizontal direction, measuring accuracies for the linear and angular motion were within ${\pm}0.02\;{\mu}m$ and ${\pm}0.04$ arcsec, respectively. In the vertical direction, they were within ${\pm}0.02{\mu}m$ and ${\pm}0.05$ arcsec. From these results, it was found that the introduced measurement method was very effective to measure 5 DOF motion errors of the ultra precision feed tables.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.4
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• pp.136-146
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• 1992

This paper provides the end-point positioning of a single-link flexible robot arm by inverse dynamics. The system is composed of a flexible arm, the mobile ballscrew stage as an arm base, a DC servomotor as an actuator, and a computer. Actuator voltages required for the model of a flexible arm to follow a given tip trajectory are formulated on the basis of the Bermoullie-Euler beam theory and solved by applying the Laplace transform method, and computed by the numerical inversion method proposed by Weeks. The mobile stage as the arm base is shifted so that the end-point follows the desired trajectories. Then the trajectory of end-point is measured by the laser displacement sensor. Here, two kinds of functions are chosen for the given tip trajectories. One is what is called the bang-bang acceleration profile and the other is the Gaussian velocity profile.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1746-1749
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• 1997

A distributed optical fiber temperature sensor can continually monitor the measurand at every point along of its fiber length. It is based on OTDR technics which used extreamlly weak backward scattered light called Raman scattering. When the Pulsed high intensity laser light injected into the optical fiber there are several kind of backscattered light such as Rayleigh, Stokes, and anti-Stokes, etc. caused by impurities molecular vibrations. The temperature distribution is derived form the intensity ratio Raman scatted light-Stokes versus anti-Stokes-and the time function between light injection and signal detection. It is shown that the priniciple of distributed sensing, the system desing, and the result of experiments.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.4
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• pp.33-39
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• 2010

Manufacturing accuracy of a precision instrument was essential to stability and efficiency of the product. Accordingly, geometrically accuracy management of precision instrument was very becoming the technique in order to design and manufacturing for machine. In this study, Measuring System is developed for extra long roller using non-contact sensor. Futhermore, It's studied by Geometric Tolerance. Exact roundness is obtained to Least Squares method from the reference circle of measured data. Measuring System is analyzed point of measurement and straightness of extra long roller is evaluated by FEM.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1102-1107
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• 2009

An ultrasonic sensor has been widely used as a range sensor for its low cost and capability of detecting some obstacles, such as glasses and black surfaces, which are not well detected by a laser scanner and an IR sensor. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to obstacle avoidance using low-cost anisotropic ultrasonic sensors with wide beam angle. In this paper, obstacles can be detected by the proposed sensor configuration which consists of one transmitter and three receivers. Because even wide obstacles are represented by a point, which corresponds to the intersection of range data from each receiver of the anisotropic sensor, a robot cannot avoid wide obstacles successfully. This paper exploits the probabilistic mapping technique to avoid collision with various types of obstacles. The experimental results show that the proposed method can robustly avoid obstacles in most indoor environments.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.87-93
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• 2019

This paper presents a 6-DOF relocalization using a 3D laser scanner and a monocular camera. A relocalization problem in robotics is to estimate pose of sensor when a robot revisits the area. A deep convolutional neural network (CNN) is designed to regress 6-DOF sensor pose and trained using both RGB image and 3D point cloud information in end-to-end manner. We generate the new input that consists of RGB and range information. After training step, the relocalization system results in the pose of the sensor corresponding to each input when a new input is received. However, most of cases, mobile robot navigation system has successive sensor measurements. In order to improve the localization performance, the output of CNN is used for measurements of the particle filter that smooth the trajectory. We evaluate our relocalization method on real world datasets using a mobile robot platform.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.429-438
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• 2011

LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.