• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.58-65
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• 2021

Most pipe-inspection robots have fixed sizes and use a wired cable system. Pipelines are generally composed of various structures, including bent pipes, vertical pipes, branch pipes, and holes, and it is difficult to explore the insides of such modular piping structures. In an offshore plant pipeline, a robot that can pass through the pipe hole in the downward direction or avoid obstacles, such as a measuring instruments, has not been introduced yet. In this study, an inspection robot that can travel through most pipelines in offshore plants is proposed. This robot uses mecanum wheels; upward, downward, and rotary motion; and a novel rotatable mechanism. Moreover, the robot is designed to be compact and lightweight to include additional devices in the middle.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.127-130
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• 2002

Human's brain action can divide by recognition and intelligence. recognition is sensing voice, image and smell and Intelligence is logical judgment, inference, decision. To this concept, Define function of cerebral cortex, and apply the result. Current expert system is lack, that reasoning by cerebral cortex and thalamus, hoppocampal and so on. In this paper, With human's brain action, wish to embody human's action artificially Embody brain mechanism using Modular Neural Network, Applied this result to snake robot.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.314-321
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• 2005

In this paper an intelligence embedding quadruped pet robot is described. It has 15 degrees of freedom and consists of various sensors such as CMOS image, voice recognition and sound localization, inclinometer, thermistor, real-time clock, tactile touch, PIR and IR to allows owners to interact with pet robot according to human's intention as well as the original features of pet animals. The architecture is flexible and adopts various embedded processors for handling sensors to provide modular structure. The pet robot is also used for additional purpose such like security, gaming visual tracking, and research platform. It is possible to generate various actions and behaviors and to download voice or music files to maintain a close relation of users. With cost-effective sensor, the pet robot is able to find its recharge station and recharge itself when its battery runs low. To facilitate programming of the robot, we support several development environments. Therefore, the developed system is a low-cost programmable entertainment robot platform.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.311-317
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• 2015

This paper is a study on how to develop service robots can easily complex software development services robot control system. User created contents based on the robot control system developed in this study is a robot drive control circuit, a sensor data processing, the status, the monitoring systems and modular system to configure the service robot operation screen from a user perspective and that can control the service robot operation As in the text-based features that can be operated to have freedom to the robot control service content. In addition, the user has the advantage that changes position by the development as well as user created contents desired by the user operating the robot control GUI (graphic user interface) also changes are possible. As a result, the service robot operator to offer a way to make the service robot can be conveniently presented in a user's point of view how to enable the development of the service robot.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.156-164
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• 2011

This paper propose a localization system of indoor mobile robots. The localization system includes camera and artificial landmarks for global positioning, and encoders and gyro sensors for local positioning. The Kalman filter is applied to take into account the stochastic errors of all sensors. Also we develop a dead reckoning system to estimate the global position when the robot moves the blind spots where it cannot see artificial landmarks, The learning engine using modular networks is designed to improve the performance of the dead reckoning system. Experimental results are then presented to verify the usefulness of the proposed localization system.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2365-2367
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• 2003

In this paper, we propose the RDC(Robot Design Center) for a network-based personal robot system. The RDC is developed under the new software framework for personal robots. The configuration for each modules in robot and functions of the RDC are described. The concept of standardized and modular program is presented and finally, developing procedures are proposed.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.131-138
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• 2020

This paper proposes a low-cost robotic surgery system composed of a general purpose robotic arm, an interface for daVinci surgical robot tools and a modular haptic controller utilizing smart actuators. The 7 degree of freedom (DOF) haptic controller is suspended in the air using the gravity compensation, and the 3D position and orientation of the controller endpoint is calculated from the joint readings and the forward kinematics of the haptic controller. Then the joint angles for a general purpose robotic arm is calculated using the analytic inverse kinematics so that that the tooltip reaches the target position through a small incision. Finally, the surgical tool wrist joints angles are calculated to make the tooltip correctly face the desired orientation. The suggested system is implemented and validated using the physical UR5e robotic arm.

• The Journal of Korea Robotics Society
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• v.3 no.4
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• pp.345-350
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• 2008

This study aims to propose the concept design of oil spill protection robot which can rapidly intervene to control the oil spillage situation at the sea. Taking into account the fact that a huge amount of oil is transported trans-continentally by oil tanker, none of industrialized countries are completely safe from the marine oil spill which results in social, economical and ecological damages to their communities. The employment of double hull-oil tanker, pipe line transporting can be most safe way. Yet complete prevention of oil spill is probably not realistic. Accordingly the alternative solution to control marine oil spill and minimize the damages caused by the incident using intelligent robot technology based on swarm control method is proposed. The main features of oil spill protection(OSP) robot is explained via following three perspectives. Firstly, from functional point of view, OSP robot system safely and efficiently replaces oil boom installation manually conducted by human workers with intelligent robot technology based on swarm control theory. For second, its modular architecture brings efficient storage of main components including oil boom and facilitates maintenance. For the last, its geometric form and shape enables whole system to be installed to helicopter, boat or oil tanker itself with ease and to rapidly deploy the units to the oil spill area.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.467-472
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• 2008

In this paper, we design, implement and apply network physical layer to 100 BaseFx optical cable interface module based on industrial ethernet protocol which is physical layer of EtherCAT that has ensure its open standard ethernet compatibility which having been provided with real time of control in network of intelligent service robot, can be process numerous data to sensor and motor control system. Through BLDC motor control performance tests, we try to propose suitability as internal network of intelligent service robot and automation system.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.139-146
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• 2002

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless these algorithms can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL) as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.