• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.329-334
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• 2011

This paper presents the method for location estimation with obstacle tracking method. A laser scanner is used to implement the system, and we assume that the map information is known. We matches the measurement of the laser scanner to estimate the location of the robot by using sequential monte carlo (SMC) method. After estimating the robot's location, the pose of obstacles are detected and tracked, hence, we can predict the collision risk of them. Finally, we present the experiment results to verify the proposed method.

• Journal of Drive and Control
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• v.16 no.2
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• pp.22-29
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• 2019

This study presented a model predictive tracking control algorithm of autonomous truck based on object state estimation using extended Kalman filter. To design the model, the 1-layer laser scanner was used to estimate position and velocity of the object using extended Kalman filter. Based on these estimations, the desired linear path for object tracking was computed. The lateral and yaw angle errors were computed using the computed linear path and relative positions of the truck. The computed errors were used in the model predictive control algorithm to compute the optimal steering angle for object tracking. The performance evaluation was conducted on Matlab/Simulink environments using planar truck model and actual point data obtained from laser scanner. The evaluation results showed that the tracking control algorithm developed in this study can track the object reasonably based on the model predictive control algorithm based on the estimated states.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.361-370
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• 2020

Automatic building material recognition has been a popular research interest over the past decade because it is useful for construction management and facility management. Currently, the extensively used methods for automatic material recognition are mainly based on 2D images. A terrestrial laser scanner (TLS) with a built-in camera can generate a set of coloured laser scan data that contains not only the visual features of building materials but also other attributes such as material reflectance and surface roughness. With more characteristics provided, laser scan data have the potential to improve the accuracy of building material recognition. Therefore, this research aims to develop a TLS-based building material recognition method by combining machine learning techniques. The developed method uses material reflectance, HSV colour values, and surface roughness as the features for material recognition. A database containing the laser scan data of common building materials was created and used for model training and validation with machine learning techniques. Different machine learning algorithms were compared, and the best algorithm showed an average recognition accuracy of 96.5%, which demonstrated the feasibility of the developed method.

• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.130-138
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• 2009

Recently, people tracking technology is being required to various area including security application. This paper suggests a method to track people with multiple laser scanners to detect the waist part of human. Multi-target model and Kalman filter based estimation are employed to track the human movement. The proposed method is applied to a novel system to monitor the entrance area and to filter out the trespasser to pass through the door without identification. Experiments for various cases are performed to verify the usefulness of the developed system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.94-101
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• 1996

When objects are scanned spatially by a laser-beam and mechanical mirror scanners, spatial information can be obtained, and then it is improtant to accurately obtain the parameters relating the light source and camera positions, etc.. In this paper, a calibration technique is presented for correction of measuremtn errors in a three-dimensional laser scanner system with two galvanometers. First, a model of the systematic errors is developed based on the geometry of the scanning system. Calibration parameter values are then iteratively adjusted with coarse-fine search in order to minimize errors (evaluation function) between measured and computed distances. It is shown that this correction method results in measurement precision suitable for practical use.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.809-817
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• 2008

This paper describes an obstacle detecting system of an unmanned ground vehicle (UGV). The unmanned ground vehicle is consists of several systems such as vehicle control system, navigation system, obstacle detecting system and integration system. Among these systems, the obstacle detecting system is a driving assistance system of UGV. Through the UGV is driving, the system detects obstacles such as cars, human, tree, curb and hills and then send information of obstacles position to integration system for safety driving. In this research, the obstacle detecting system is composed of 5 laser scanners and develop algorithms of detecting obstacles, curb, uphill and downhill road.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.829-836
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• 2000

High performance laser printer requires high speed scanning motor, which can operate up to 40,000 rpm. However, development of high speed scanning motor has been restricted due to the practical problems such as use of high speed bearing, compact circuit design and high cost. In this study, we designed a high speed scanner motor for use on laser scanning unit and discussed some design principles including the reduction method of cogging torque of the motor, development of hemispherical aerodynamic bearing, windage loss estimation, and operating circuit design to reduce noise.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.393-398
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• 2002

This study proposes a method to reduce error scanning data of laser scanner. The method co of 3 stages. First, there is an error indu difference of the distance between the prob the object. It is possible to reduce the e planning a scanning strategy: object settin path. Second, the scan data loss of the tooli affects calculating the tooling ball con z-direction compensation is given to calculat accurate registration points. Third, three p used to determine a transformation matrix on frame. As merging, the maximum error usually on the third tooling ball in the conven method, which select a point among three po randomly. We find the centroid of 3 points apply it to determine a new transformation mat

• Tunnel and Underground Space
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• v.17 no.3 s.68
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• pp.165-174
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• 2007

The technique, which reproduces the figures of objects from measured data of the objects using 3-D laser scanner, is called reverse engineering. Recently, research studies into applications of reverse engineering to rock engineering are increasing in number, in the discontinuity surveys for rock slopes out of man's reach, or rapid discontinuity surveys for wide range areas. For analysis of discontinuity using reverse engineering, a program for processing point clouds data from the 3-D laser scanner, for sampling from these point clouds data, and finally analyzing the discontinuity is needed. However, existing programs rarely have sufficient functions to properly analyze the discontinuities. In this study, a program was developed, which can automatically sample discontinuities from the point clouds data which measured in a rock slope using a 3-D laser scanner, and which can also undertake statistical analysis of the discontinuities. This developed program was verified by the application of discontinuity surveys in a rock slope and a tunnel. By undertaking the discontinuity survey using a 3-D laser scanner and the developed program, the feasibility and rapidity of such surveys is expected to improve in areas out of man's reach in geotechnical surveys. Taking into consideration the fact that the international level of related techniques is at a rudimentary stage, the possibility of prior occupation of a broad market is also expected.

• Computers and Concrete
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• v.33 no.5
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• pp.595-603
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• 2024

In the construction industry, there has been a surge in the implementation of high-tech equipment in recent years. Various technologies are being considered as potential solutions for future construction projects. Building information modeling (BIM), which utilizes advanced equipment, is a promising solution among these technologies. The need for safety inspection has also increased with the aging structures. Nevertheless, traditional safety inspection technology falls short of meeting this demand as it heavily relies on the subjective opinions of workers. This inadequacy highlights the need for advancements in existing maintenance technology. Research on building safety inspection using 3D laser scanners has notably increased. Laser scanners that use light detection and ranging (LiDAR) can quickly and accurately acquire producing information, which can be realized through reverse engineering by modeling point cloud data. This study introduces an innovative evaluation system for building safety using a 3D laser scanner. The system was used to assess the safety of an existing three-story building by implementing a reverse engineering technique. The 3D digital data are obtained from the scanner to detect defects and deflections in and outside the building and to create an as-built BIM. Subsequently, the as-built structural model of the building was generated using the reverse engineering approach and used for structural analysis. The acquired information, including deformations and dimensions, is compared with the expected values to evaluate the effectiveness of the proposed technique.