• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.260-269
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• 2021

To verify performance or conduct experiments using actual robots, a lot of costs are needed such as robot hardware, experimental space, and time. Therefore, a simulation environment is an essential tool in robotics research. In this paper, we develop the HUMIC simulator using ROS and Gazebo. HUMIC is a humanoid robot, which is developed by HCIR Lab., for human-robot interaction and an upper body of HUMIC is similar to humans with a head, body, waist, arms, and hands. The Gazebo is an open-source three-dimensional robot simulator that provides the ability to simulate robots accurately and efficiently along with simulated indoor and outdoor environments. We develop a GUI for users to easily simulate and manipulate the HUMIC simulator. Moreover, we open the developed HUMIC simulator and GUI for other robotics researchers to use. We test the developed HUMIC simulator for object detection and reinforcement learning-based navigation tasks successfully. As a further study, we plan to develop robot behavior intelligence based on reinforcement learning algorithms using the developed simulator, and then apply it to the real robot.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.775-778
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• 2007

로봇의 응용과 활용분야는 현 산업의 주요 이슈가 되고 있다. 현재 싱글로봇의 효율적인 운영을 넘어 넓은 공간에서 중복적인 공간 탐색을 최소화하기 위한 멀티 로봇 운영 기법은 중요한 연구 주제 중에 하나로 부각되고 있다. 멀티 로봇을 효율적으로 운영하기 위해서는 멀티 로봇 시스템의 각 싱글 로봇의 움직임을 파악하여 효율적으로 업무를 할당 할 수 있는 관리체계가 필요하다. 멀티 로봇의 업무 할당과 중복 탐색 최소화를 위해 본 논문에서는 중앙 서버와 RFID 시스템을 이용한 청소 멀티 로봇 운영 기법을 제안한다. 제안한 시스템은 로봇의 localization, navigation 및 mapping을 효율적으로 수행하기 위해 RFID를 활용하고 최적의 청소 공간 할당을 위하여 중앙 서버가 멀티 로봇을 효율적으로 관리한다. 청소 멀티 로봇 시스템에서는 싱글 로봇과 비교하여 효율적인 로봇의 운영을 보장할 뿐만 아니라 각 싱글 로봇의 상태와 주변 상태를 고려한 fault-tolerance를 제공함으로써 로봇 운영의 신뢰성을 보장할 수 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.94-106
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• 2020

Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.187-194
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• 2016

When performing experiments in indoor and outdoor environment, we need a system that monitors a volunteer to prevent dangerous situations and efficiently manages the data in real time. We developed a guidance device for visually impaired person that guides the user to walk safely to the destination in the previous study. We set a POI (Point of Interest) of a specific location indoors and outdoors and tracks the user's position and navigate the walking path using artificial markers and ZigBee modules as landmark. In addition, we develop path finding algorithm to be used for navigation in the guidance device. In the test bed, the volunteers are exposed to dangerous situations and can be an accident due to malfunction of the device since they are visually impaired person or normal person wearing a eye patch. Therefore the device requires a system that remotely monitors the volunteer wearing guidance device and manages indoor or outdoor a lot of map data. In this paper, we introduce a managing system that monitors the volunteers remotely and handles map data efficiently. We implement a management system which can monitor the volunteer in order to prevent a hazardous situation and effectively manage large amounts of data. In addition, we verified the effectiveness of the proposed system through various experiments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.655-663
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• 2017

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.

• 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.

• Korean Journal of Optics and Photonics
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• v.29 no.5
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• pp.204-214
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• 2018

Since LIDAR is advantageous for accurate information acquisition and realization of a high-resolution 3D image based on characteristics that can be precisely measured, it is essential to autonomous navigation systems that require acquisition and judgment of accurate peripheral information without user intervention. Recently, as an autonomous navigation system applying LIDAR has been utilized in human living space, it is necessary to solve the eye-safety problem, and to make reliable judgment through accurate obstacle recognition in various environments. In this paper, we construct a single-shot LIDAR system (SSLs) using a 1550-nm eye-safe light source, and report the analysis method and results of LIDAR signals for various measurement environments, reflective materials, and material angles. We analyze the signals of materials with different reflectance in each measurement environment by using a 5% Al reflector and a building wall located at a distance of 25 m, under indoor, daytime, and nighttime conditions. In addition, signal analysis of the angle change of the material is carried out, considering actual obstacles at various angles. This signal analysis has the merit of possibly confirming the correlation between measurement environment, reflection conditions, and LIDAR signal, by using the SNR to determine the reliability of the received information, and the timing jitter, which is an index of the accuracy of the distance information.

• Journal of Navigation and Port Research
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• v.34 no.1
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• pp.15-19
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• 2010

Recently, the wireless LAN system is rapidly growing because of its convenience of high speed communication. However, the wireless LAN systems at indoor places occur multi-propagation path by reflected waves from walls, ceilings, floors, and desks. Multipath problems cause transmission errors and degradation of communication speed. These problems can be solved by using EM wave absorbers. In this paper, we analyzed property of Graphite and derived the optimum ratio of Graphite: CPE to develop EM wave absorber for the wireless LAN system. First, we fabricated several samples in different composition ratios of Graphite and CPE, and then measured the reflection coefficient of each samples. Material constants of permittivity and permeability were calculated using the measured data and designed EM wave absorber. Secondly, the EM wave absorber was fabricated and tested on the base of the simulation data. As a result, it showed that the EM wave absorber in 1.7 mm thickness with the ratio of Graphite: CPE=50:50 wt.% has excellent absorption ability more than 27 dB at 5.2 GHz.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.421-426
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• 2018

With regard to LED lighting devices which have currently been commercialized, LED operating sequences are being sold in a fixed state. In such a state, the external environmental factors are not taken into consideration as only the illumination environment application is considered. Currently, it is difficult to create an optimal lighting environment which can adapt to changes in external environmental factors in the ship. Therefore, it was concluded that there is a need to input the external environment value so that the optimal illumination value can be reflected in real time in order to adapt more organically and actively to the change of external environmental factors. In this paper, we used a microprocessor as an integrated management system for environmental data that changes in real time according to existing external environmental factors. In addition, a controller capable of lighting control of RGB LED module by combining fuzzy inference system. For this, a fuzzy control algorithm is designed and a fuzzy control system is constructed. The distance and the illuminance value from the external environment element are input to the sensor, and these values are converted to the optimum illumination value through the fuzzy control algorithm, and are expressed through the dimming control of the RGB LED module and the practical effectiveness of the fuzzy control system is confirmed.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.