• IEMEK Journal of Embedded Systems and Applications
• /
• v.16 no.3
• /
• pp.107-111
• /
• 2021

A 3D point cloud map is an essential elements in various fields, including precise autonomous navigation system. However, generating a 3D point cloud map using a single sensor has limitations due to the price of expensive sensor. In order to solve this problem, we propose a precise 3D mapping system using low-cost sensor fusion. Generating a point cloud map requires the process of estimating the current position and attitude, and describing the surrounding environment. In this paper, we utilized a commercial visual-inertial odometry sensor to estimate the current position and attitude states. Based on the state value, the 2D LiDAR measurement values describe the surrounding environment to create a point cloud map. To analyze the performance of the proposed algorithm, we compared the performance of the proposed algorithm and the 3D LiDAR-based SLAM (simultaneous localization and mapping) algorithm. As a result, it was confirmed that a precise 3D point cloud map can be generated with the low-cost sensor fusion system proposed in this paper.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.3
• /
• pp.521-526
• /
• 2023

Due to the recent pandemic, most educational systems are being conducted through online classes. Unlike face-to-face classes, it is even more difficult for learners to maintain concentration, and evaluating the learners' attitude toward the class is also challenging. In this paper, we proposed a real-time concentration-based review support system for learners in real-time video lectures that can be used in online classes. This system measured the learner's face, pupils, and user activity in real-time using the equipment used in the existing video system, and delivers real-time concentration measurement values to the instructor in various forms. At the same time, if the concentration measurement value falls below a certain level, the system alerted the learner and records the timestamp of the lecture. By using this system, instructors can evaluate the learners' participation in the class in real-time and help to improve their class abilities.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.4
• /
• pp.398-404
• /
• 2015

In this paper, we describe the design and performance of a prototype multi-rotor unmaned aerial vehicle( UAV) platform featuring an inertial measurement unit(IMU) based autonomous-flying for use in bluetooth communication environments. Although there has been a fair amount of study of free-flying UAV with multi-rotors, the more recent trend has been to outfit hexarotor helicopter with gimbal to support various services. This paper introduces the hardware and software systems toward very compact and autonomous hexarotors, where they can perform search, rescue, and surveillance missions without external assistance systems like ground station computers, high-performance remote control devices or vision system. The proposed system comprises the construction of the test hexarotor platform, the implementation of an IMU, mathematical modeling and simulation in the helicopter. Furthermore, the hexarotor helicopter with implemented IMU is connected with a micro controller unit(MCU)(ARM-cortex) board. The micro-controller is able to command the rotational speed of the rotors and to get the measurements of the IMU as input signals. The control simulation and experiment on the real system are implemented in the test platform, evaluated and compared against each other.

• Smart Structures and Systems
• /
• v.20 no.4
• /
• pp.397-413
• /
• 2017

Precast concrete (PC) members are currently being employed for general construction or partial replacement to reduce construction period. As assembly work in PC construction requires connecting PC members accurately, measuring the 6-DOF (degree of freedom) relative displacement is essential. Multiple planar markers and camera-based displacement measurement systems can monitor the 6-DOF relative displacement of PC members. Conventional methods, such as direct linear transformation (DLT) for homography estimation, which are applied to calculate the 6-DOF relative displacement between the camera and marker, have several major problems. One of the problems is that when the marker is partially hidden, the DLT method cannot be applied to calculate the 6-DOF relative displacement. In addition, when the images of markers are blurred, error increases with the DLT method which is employed for its estimation. To solve these problems, a hybrid method, which combines the advantages of the DLT and MCL (Monte Carlo localization) methods, is proposed. The method evaluates the 6-DOF relative displacement more accurately compared to when either the DLT or MCL is used alone. Each subsystem captures an image of a marker and extracts its subpixel coordinates, and then the data are transferred to a main system via a wireless communication network. In the main system, the data from each subsystem are used for 3D visualization. Thereafter, the real-time movements of the PC members are displayed on a tablet PC. To prove the feasibility, the hybrid method is compared with the DLT method and MCL in real experiments.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.4
• /
• pp.14-19
• /
• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.3
• /
• pp.697-705
• /
• 2014

This paper presents a vision based object width measurement method and its application where the light sectioning method is employed. The target object for measurement is a tread, which is the most outside component of an automobile tire. The entire system applying the measurement method consists of two processes, i.e. a calibration process and a detection process. The calibration process is to identify the relationships between a camera plane and a laser plane, and to estimate a camera lens distortion parameters. As the process requires a test pattern, namely a jig, which is elaborately manufactured. In the detection process, first of all, the region that a laser light illuminates is extracted by applying an adaptive thresholding technique where the distribution of the pixel brightness is considered to decide the optimal threshold. Then, a thinning algorithm is applied to the region so that the ends and the shoulders of a tread are detected. Finally, the tread width and the shoulder width are computed using the homography and the distortion coefficients obtained by the calibration process.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2006.06a
• /
• pp.543-544
• /
• 2006

This paper describes a simple real-time monitoring system for use in measurement subsystem of contact wire and geometry of overhead contact wire in electric railway. The system has been consists of a high speed CMOS camera with resolution $1024\;{\times}\;1280$ pixels, line type laser source with a power equal to 300 mW, and PC-based image acquisition system with PCI Express slot. National instrument LabVIEW (8.0) and vision acquisition software have been used in application programming interface for image acquisition, display, and storage with a frequency of sampling of 500 acquisitions per second.

• Electronics and Telecommunications Trends
• /
• v.28 no.6
• /
• pp.127-132
• /
• 2013

본 논문에서는 야간 및 해무 상태에서 선박의 안전 운항을 지원할 수 있는 해상 적외선 스테레오비전 대구경 감시 시스템용 거리 측정 기법을 제안하였다. 선박의 안전 운항을 위한 감시 시스템에는 스테레오비전 정보를 이용하여 거리를 측정하는 알고리즘이 필요하며 물체의 이미지 및 물체까지의 거리정보를 디스플레이 하는 기능을 구현하였다. 원거리 측정 및 야간 측정 기능을 구현하기 위해 적외선 스테레오비전 및 대구경 렌즈를 이용하였으며, 행상에서 파고에 의한 흔들림으로 이미지의 연속적인 처리가 어려운 측면이 있어 물체의 비전 정보를 이용하여 거리를 계산하는 알고리즘 및 계산된 거리 정보를 디스플레이하는 프로그램을 개발하였다. 이러한 실험 결과가 선박 안전운항을 위한 유용한 시스템이 될 것으로 예상하고 있다.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.525-528
• /
• 2003

In this paper, we present a novel idea to integrate low cost Inertial Measurement Unit(IMU) and Differential Global Positioning System (DGPS) for Telematics applications. As well known, low cost IMU produces large positioning and attitude errors in very short time due to the poor quality of inertial sensor assembly. To conquer the limitation, we present a bimodal approach for integrating IMU and DGPS, taking advantage of positioning and orientation data calculated from CCD images based on photogrammetry and stereo-vision techniques. The positioning and orientation data from the photogrammetric approach are fed back into the Kalman filter to reduce and compensate IMU errors and improve the performance. Experimental results are presented to show the robustness of the proposed method that can provide accurate position and attitude information for extended period for non-aided GPS information.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.151-158
• /
• 2006

Structural health monitoring is concerned with the safety and serviceability of the users of structures, especially for the case of building structures and infrastructures. When considering the safety of a structure, the maximum stress in a member due to live load, earthquake, wind, or other unexpected loadings must be checked not to exceed the stress specified in a code. It will not fail at yield, excessively large displacements will deteriorate the serviceability of a structure. To guarantee the safety and serviceability of structures, the maximum displacement in a structures must be monitored because actual displacement is a direct assessment index on its stiffness. However, no practical method has been reported to monitor the displacement, especially for the case of displacement of high-rise buildings because of not to easy accessive. In this paper, it is studied displacement measuring method of high-rise buildings using LiDAR The method is evaluated by analyzing accuracy of measured displacements for existing building.