• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.235-240
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.332-340
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• 2013

This paper reports a programming toolkit for implementing localization and navigation of a mobile robot both in real world and simulation. Many of the previous function libraries are difficult to use because of their complexity or lack of usability. The proposed toolkit consist of functions for dead reckoning, motion model, measurement model, and operations on directions or heading angles. The dead reckoning and motion model deals with differential drive robot and bicycle type robot driven by front wheel or rear wheel. The functions can be used for navigation in both real environment and simulation. To prove the feasibility of the toolkit, simulation results are shown along with the results in real environment. It is expected the proposed toolkit is used for test of algorithms for mobile robot navigation such as localization, map building, and obstacle avoidance.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.4
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• pp.62-67
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized loaming architecture. It is Proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tucking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.12 s.189
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• pp.46-55
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• 2006

A robust motion controller based on self-organizing fuzzy control(SOFC) and feed-back tracking control technique is proposed for a two-wheel driven mobile robot. The feed-back control technique of the controller guarantees the robot follows a desired trajectory. The SOFC technique of the controller deals with unmodelled dynamics of the vehicle and uncertainties. The computer simulations are carried out to verify the tracking ability of the proposed controller with various driving situations. The results of the simulations reveal the effectiveness and stability of the proposed controller to compensate the unmodelled dynamics and uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.171.2-171
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• 2001

This paper presents a force control of a arm of walking training robot. The current gait training apparatus in hospital are ineffective for the difficulty in keeping constant unloading level and constraining patients to walk freely. The proposed walking training robot is designed to unload body weight effectively during walking. The walking training robot consists of unloading manipulator and mobile platform. The manipulator driven with a electro-mechanical linear mechanism unloads body weight in various level. The mobile platform is wheel type, which allows to patients unconstrained walking. Unloading system with electro-mechanical linear mechanism has been developed, which has advantages such as low noise level, light weight, low manufacturing cost and low power consumption. A system model for the manipulator ...

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.312-318
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• 2003

We propose a new technique for the cruise control system design of a mobile robot with three drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized teaming architecture. It is proposed a learning controller consisting of too neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by three independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.207-212
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• 2004

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of IKEEE
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• v.18 no.4
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• pp.572-580
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• 2014

This study deals with reconfigurable modular robot with respect to the compact and capability of representing the various actions for promoting creativity through education and play. Generally modular robot can be designed as a suitable robot that is transformed to various structure by reconstructing each cells, However, there are only few research on the education and play using those robots in the world and still nothing domestically. Unlike the existing modular robots only having a repeating motion, the proposed modular works by individual module such as sound is produced by sound module, wheel is driven by wheel module, LED module controls the visual expression, power is supplied by battery module, bluetooth module for communication, and dynamic motion realization is possible by using joint module. By manipulating the abilities endowed by individual modules, diversity of creative activities is possible and thus made an easy access for children. This study deals with the design of modular robotic by using the variety of different modules to endowed the learning and playing ability. And the study showed the utility of the operating behavior over the actual production and testing.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.528-531
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• 1997

This paper deals with the kinematic and dynamic modeling of a 3 degree-of-freedom redundantly actuated mobile robot for the purpose of analysis and control. Each wheel is driven by two motors for steering and driving. Therefore, the system becomes force-redundant since the number of input variable is greater than the number of output variable. The kinematic and dynamic models in terms of three independent joint variables are derived. Also, a load distribution method to determine the input loads is introduced. Finally we demonstrate the feasibility of the proposed algorithms through simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1804-1807
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• 1997

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learnign architecture. It is proposed a learning controller consisting of two neural networks-fuzzy based on independent reasoning and a connecton net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.