• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1115-1120
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• 2003

The present paper shows the possible development of particle swarm optimization (PSO) based fuzzy-neural networks (FNN) which can be employed as an important building block in real life robot systems, controlled by voice-based commands. The PSO is employed to train the FNNs which can accurately output the crisp control signals for the robot systems, based on fuzzy linguistic spoken language commands, issued by an user. The FNN is also trained to capture the user spoken directive in the context of the present performance of the robot system. Hidden Markov Model (HMM) based automatic speech recognizers are developed, as part of the entire system, so that the system can identify important user directives from the running utterances. The system is successfully employed in a real life situation for motion control of a redundant manipulator.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.411-414
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• 2003

Particle swarm optimization (PSO) is employed to train fuzzy-neural networks (FNN), which can be employed as an important building block in real life robot systems, controlled by voice-based commands. The FNN is also trained to capture the user spoken directive in the context of the present performance of the robot system. The system has been successfully employed in a real life situation for navigation of a mobile robot.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.55-60
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• 2021

As the smart factory progresses, the use of automation facilities and robots is increasing. Also, with the development of IT technology, the utilization of the system using voice recognition is also increasing. Voice recognition technology is a technology that stands out in smart home and various IoT technologies, but it is difficult to apply to factories due to the specificity of factories. Therefore, in this study, a method to control an industrial articulated robot was designed using voice recognition technology that considers the situation at the manufacturing site. It was confirmed that the robot could be controlled through network protocol and command conversion after receiving voice commands for robot operation through mobile.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1938-1943
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• 2005

Network human-robot interface is an important research topic. In home application, users access the robotic system directly via voice, gestures or through the network. Users explore a system by using the services provided by this system and to some extend users are enable to participate in a service as partners. A service may be provided by a robot, a group of robots or robots and other network connected systems (distributed sensors, information systems, etc). All these services are done in the network environment, where uncertainty such as the unstable network connection, the availability of the partners in a service, exists. Moreover, these services are controlled by several users, accessing at different time by different methods. Our research aimed at solving this problem to provide a high available level, flexible coordination system. In this paper, a multi-agent framework is proposed. This framework is validated by using our new concept of slave agents, a responsive multi-agent environment, a virtual directory facilitator (VDF), and a task allocation system using contract net protocol. Our system uses a mixed model between distributed and centralized model. It uses a centralized agent management system (AMS) to control the overall system. However, the partners and users may be distributed agents connected to the center through agent communication or centralized at the AMS container using the slave agents to represent the physical agents. The system is able to determine the task allocation for a group of robot working as a team to provide a service. A number of experiments have been conducted successfully in our lab environment using Issac robot, a PDA for user agent and a wireless network system, operated under our multi agent framework control. The experiments show that this framework works well and provides some advantages to existing systems.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.99-113
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• 2020

In the future, robots and drones for the convenience of our lives in everyday life will increase. As a method for controlling this, a remote control or a human voice method is most commonly used. However, the remote control needs to be operated by a person and can not ignore ambient noise in the case of voice. In this paper, we propose an economical attitude information acquisition method to accurately acquire the posture information of the arm in real time under the assumption that the surround drones or robots can be controlled wirelessly with the posture information of the arm. For this purpose, the extended Kalman filter was used to eliminate the noise of the arm position information. in order to detect the arm movement, a low cost MEMS type sensor was applied to secure the economical efficiency of the apparatus. To increase the wear ability of the arm, We developed a compact and lightweight attitude information acquisition system by integrating all functions into one chip as much as possible. As a result, the real-time performance of 1 ms was secured and the extended Kalman filter was applied to acquire the accurate attitude information of the arm with noise removed and display the attitude information of the arm in real time. This provides a basis for generating commands using real-time attitude information of the arm.