• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.205-206
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• 2021

본 논문에서는 ROS를 이용한 드론 군집 비행 시뮬레이션을 구현한 결과를 보인다. ROS 환경에서 Gazebo 시뮬레이션 툴과 ArduPilot을 이용하여 모델링된 드론을 Gazebo에 적용한 뒤, 프로그래밍된 명령을 적용하여 각각의 드론이 명령에 따라 제어되는 군집비행을 보인다. 시뮬레이션은 12대의 드론이 각각 cpp 파일에 따라 제어되도록 설정한 launch 파일을 roslaunch하여 설정한 모든 드론이 Gazebo에서 각각 제어되는 군집비행 시뮬레이션을 구현하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.271-272
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• 2021

본 논문에서는 Gazebo 시뮬레이터 기반 UAV 군집 시뮬레이션 구현 및 비행 고도 계층화를 구현한 결과를 보인다. Gazebo 시뮬레이션과 Autopilot Program인 Pixhawk4 SITL(Software In The Loop)을 이용하여 UAV를 시뮬레이터에 생성한 뒤 사전에 정의된 Mission에 대한 정보에 따라 비행이 되도록 구현하였다. 또한, Gazebo 시뮬레이터의 Box Object를 이용하여 UAV의 비행 고도를 시각적으로 계층화하여 표현하였다.

• 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.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_2
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• pp.265-272
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• 2023

In this paper, we directly implemented the Line Tracer ROS package that can detect and follow lines drawn on the map on Gazebo, an open-source that is widely used in autonomous driving research. For line detection, the cv_bridge package was used to enable OpenCV's image processing tools, and parameters such as robot speed, line color and ground material could be changed. In addition, proportional (P) and PID controls could be implemented using the color centroid obtained through image processing. Through this approach, the effect of proportional and differential coefficients on the robot's line tracer motion could be analyzed effectively. In addition, by displaying robot simulation results using various tools of ROS, an efficient development for control nodes could be established in ROS.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.103-110
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• 2023

In order for future UAVs to be used as means of transportation, a simulation environment in which they can be tested in advance is essential. Accordingly, to demonstrate future air transport systems among six future industries of Chungcheongbuk-do, a simulation environment was condensed and built, focusing on virtual safety corridor connecting Osong Station and Cheongju Airport.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.95-100
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• 2021

This paper introduces model-based meta reinforcement learning as a control for the manipulator of an underwater construction robot. Model-based meta reinforcement learning updates the model fast using recent experience in a real application and transfers the model to model predictive control which computes control inputs of the manipulator to reach the target position. The simulation environment for model-based meta reinforcement learning is established using MuJoCo and Gazebo. The real environment of manipulator control for underwater construction robot is set to deal with model uncertainties.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.441-450
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• 2022

The introduction of autonomous underwater gliders (AUGs) specifically addresses the reduction of operational costs that were previously prohibited with conventional autonomous underwater vehicles (AUVs) using a "scaling-down" design philosophy by utilizing the characteristics of autonomous drifters to far extend operation duration and coverage. Long-duration, wide-area missions raise the cost and complexity of in-water testing for novel approaches to autonomous mission planning. As a result, a simulator that supports the rapid design, development, and testing of autonomy solutions across a wide range using software-in-the-loop simulation at faster-than-real-time speeds becomes critical. This paper describes a faster-than-real-time AUG simulator that can support high-resolution bathymetry for a wide variety of ocean environments, including ocean currents, various sensors, and vehicle dynamics. On top of the de facto standard ROS-Gazebo framework and open-sourced underwater vehicle simulation packages, features specific to AUGs for ocean mapping are developed. For vehicle dynamics, the next-generation hybrid autonomous underwater gliders (Hybrid-AUGs) operate with both the buoyancy engine and the thrusters to improve navigation for bathymetry mappings, e.g., line trajectory, are is implemented since because it can also describe conventional AUGs without the thrusters. The simulation results are validated with experiments while operating at 120 times faster than the real-time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.255-256
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• 2019

본 논문에서는 물체를 집기(picking) 위해 필요한 깊이 값을 특수카메라인 리얼센스를 사용하여 받아와서 2D 카메라로는 하지 못하는 로봇 팔 피킹 시스템을 구현하였다. 객체 인식은 텐서플로우 객체 검출 라이브러리를 사용하여 정확도를 높였고, ROS 기반의 rviz, moveit, gazebo 등의 패키지를 사용하여 아두이노와 통신하며 로봇팔 하드웨어로 인식된 객체를 피킹하는 시스템을 구현하였다.

• Journal of IKEEE
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• v.22 no.2
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• pp.362-368
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• 2018

This paper has implemented a mutual conversion system that mutually converts between body motion signals and both visual and auditory signals. The present study is based on intentional synesthesia that can be perceived by learning. The Euler's angle was used in body movements as the output of a wearable armband(Myo). As a muscle sense, roll, pitch and yaw signals were used in this study. As visual and auditory signals, MIDI(Musical Instrument Digital Interface) signals and HSI(Hue, Saturation, Intensity) color model were used respectively. The method of mutual conversion between body motion signals and both visual and auditory signals made it easy to infer by applying one-to-one correspondence. Simulation results showed that input motion signals were compared with output simulation ones using ROS(Root Operation System) and Gazebo which is a 3D simulation tool, to enable the mutual conversion between body motion information and both visual and auditory information.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.2
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• pp.139-147
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• 2010

This study monitored a variety of marine fish communities in artificial reefs unit of the total 5 types (Dice type, Octagonal turtle type, Two-stage tube type, Gazebo type, Tetrapod type) which are located in the marine ranching at Jeju island by scuba diving in May, July, October and December 2009. Underwater photographing was accomplished at total 3 phases (condition of artificial reefs photographing, concentric circle movement photographing and line transect photographing). The preservation condition of artificial reefs facility was very good, and the dominant species were Chromis notatus, Sebastes thompsoni, Oplegnathus fasciatus and Halichoeres poecilopterus. Fish abundance was high in May and June, and low in October and December, 2009. Chromis notatus was dominant at the all types of artificial reefs, Halichoeres poecilopterus for Gazebo type and Tetrapod type of artificial reefs, and Sebastes thompsoni for Dice type, Octagonal turtle type and Two-stage tube type of artificial reefs.