• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.165-171
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• 2014

In this paper, we propose the hardware and software of a test-bed of a hovering AUV (autonomous underwater vehicle). Test-bed to develop as the underwater robot for the hovering -type is planning to apply for marine resource development and exploration for deep sea. The RTU that controls a azimuth thruster and a vertical thruster of test-bed is a intergrated-type thruster. The main control unit that collects sensor's data and performs high-speed processing and controls a movement of test-bed is a underwater hybrid navigation system. Also it transfers position, posture, state information of test-bed to the host PC of user using a wireless communication. The host PC checks a test-bed in real time by using a realtime monitoring system that is implemented by LabVIEW.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.343-353
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• 1995

The path navigation of autonomous guided vehicle(AGV) or autonomous mobile robot(AMR) assumed that the environment was completely known and the obstacles were fixed. So that, in an environment only partly known or not known at all, the previous works were not successful since the path exploration techniques involved in the work were neither directly applicable nor extensible. In order to improve such problems, this paper was adopted the quadtree technique and proposed the algorithm for an optimal path planning autonomously in an environment and proved a validity through a simulation.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.239-245
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• 2020

With the recent revised curriculum, the importance of exploring children's play through new teaching media is increasing in kindergarten. In this study, it is to use the robot 'Bee-bot' for early children to uncover the changes that children have through free exploration and play. As a result of comparing the change of scientific problem-solving ability of 3, 4, and 5-year-olds, there were significant changes in all three sub-elements. We propose to us scientific problem-solving ability test tools, propose and apply ideas for problem-solving, conclusion on problem-solving Building. Through this, it was found that unplugged play using 'Bee-bot' is meaningful as a play environment and as a teaching medium for children aged 3, 4 and 5 years old.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2152-2156
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• 2011

In this paper, we propose the novel behavior control algorithm by using the efficient searching method based on the characteristic of the swarm robots in unknown space. The proposed method consists of identifying the position and moving state of a robot by the dynamic modelling of a wheel drive vehicle, and planing behavior control rules of the swarm robots based on the sensor range zone. The cooperative search for unknown space is carried out by the proposed behavior control. Finally, some experiments show the effectiveness and the feasibility of the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.440-442
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• 2019

메카넘 휠과 4족 및 6족의 다리를 갖는 탐사 및 재난 로봇을 바탕으로 휠과 6족이 함께 존재하는 탐사 및 재난 로봇이다. 평지나 완만한 길에선 메카넘 휠을 이용해 빠르게 굴러가는 모습을 볼 수 있다. 그리고 계단이나 산악지대 같은 경사가 높고 휠로 이동하기 힘든 공간은 부착된 6족 다리를 이용해 걸어 나가는 모습을 볼 수 있다. 이러한 휠과 6족이 결합된 탐사 및 재난 로봇은 사람의 조종 없이 영상처리와 여려가지 센서를 이용해 스스로 자율주행 하는 모습을 볼 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.527-530
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• 2010

효과적으로 군집 로봇을 제어하기 위해 리더 로봇을 선정하여 특별한 역할을 부여하는 방법이 보편적으로 사용되고 있다. 본 논문에서는 효과적인 지형 탐사를 위해 군집 로봇 그룹의 리더를 관리하는 방법을 제안한다. 그룹에 리더가 없는 경우와 리더를 선정한 경우로 나누어 2차원 지형을 탐사하는 실험을 수행하였다. 지형을 탐사하는 과정에서 리더 로봇이 동작 불능 상태가 되는 경우가 발생할 수도 있는데, 이때에는 그룹의 리더를 교체하는 방법을 사용하였다. 그룹의 리더를 관리하는 방법을 시뮬레이션 환경에 적용하여 실험한 결과, 리더가 없는 경우보다 지형 탐사 성공률이 훨씬 높아지는 것을 알 수 있었다.

• The Journal of Korean Association of Computer Education
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• v.17 no.2
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• pp.65-76
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• 2014

This paper aims at implementing experimental devices with which middle school students can explore scientific ideas using GoGo Board and NetLogo that connect real and simulated worlds. Related research literature was reviewed to design a simulation-based learning model using computer simulation and robot-related activities. In order to construct devices for exploratory experiments, GoGo Board was adopted for developing the interface of Micro-Based Laboratory(MBL) devices with several sensors while NetLogo was used for connecting MBL devices (real world) and simulated experiments (virtual world). The simulation contents were developed in the area of heat equilibrium for changing temperature and the conduct-current relationship appeared in the textbook of middle school science class. With the developed device and contents students can visualize the change of temperature cold and hot waters in terms of heat equilibrium. They also can measure the change of conductor representing the relationship between conductor and current. The formative evaluation of the contents carried out with several middle school students indicated the future direction for upgrading simulation contents and interface. The results might be beneficial for science educators who want to apply simulation contents with the use of computers.

• Journal of the Korean School Mathematics Society
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• v.26 no.1
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• pp.49-70
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• 2023

This study aimed to design a robot programming lecture for pre-service mathematics teachers to improve their TPACK-P (TPACK-Programming) and analyze its effectiveness. The lecture design involved stages of analysis, exploration, primary micro-teaching, and secondary micro-teaching, with each stage including design, application, and evaluation. The TPACK-P survey was conducted before and after the lecture, and the results indicated a statistically significant difference in TCK at the 1% significance level and TPK, TRACK, and TRACK(P) at the 5% significance level. Further analysis using dependent sample t-tests showed that the post-test mean was significantly higher than the pre-test mean in categories such as TCK, TPK, TPACK, and TPACK(P). These findings suggest that the designed lecture positively affected the growth of pre-service mathematics teachers' TPACK-P.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.3
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.

• Electronics and Telecommunications Trends
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• v.35 no.3
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• pp.1-8
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• 2020

Artificial-intelligence (AI) technology is used in a variety of fields, from robot cleaner motion control to call center counselors, AI speakers, and Mars exploration. Because the technology levels of all applications and services that utilize AI vary widely, it is not possible to view all applications using AI technology at the same level. Nevertheless, there have been no cases in which the level of AI technology was defined. Therefore, the Electronics and Telecommunications Research Institute (ETRI) Artificial Intelligence Research Laboratory has defined the levels of the main technical elements of AI from steps 1 to 6. In this report, the Artificial Intelligence Technology Level 1.0 (ATL 1.0) is presented. It was established by comprehensively referring to the AI technology prospects and technology roadmaps of major countries. It is hoped that it can be used as a measure for determining the levels of AI applications or services or as an indicator for establishing a technology roadmap.