• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.470-477
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• 2009

Modular reconfigurable robots with physical docking capability easily adapt to a new environment and many studies are necessary for the modular robots. In this paper, we propose a vision-based fuzzy autonomous docking controller for the modular docking robots. A modular docking robot platform which performs real-time image processing is designed and color-based object recognition method is implemented on the embedded system. The docking robot can navigate to a subgoal near a target robot while avoiding obstacles. Both a fuzzy obstacle avoidance controller and a fuzzy navigation controller for subgoal tracking are designed. We propose an autonomous docking controller using the fuzzy obstacle avoidance and navigation controllers, absolute distance information and direction informations of robots from PSD sensors and a compass sensor. We verify the proposed docking control method by docking experiments of the developed modular robots in the various environments with different distances and directions between robots.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.6
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• pp.604-611
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• 2009

Modular snake-like robots are robust for failure and have flexible locomotion for environments, but are difficult to control. Various phase and evolutionary approaches for modular robots have been studied for many years, but there are few comparisons among these methods. In this paper, Phase, GAps, GA and GP approaches are implemented and compared for flat, stairs, and slope environments. In addition, simulations of the locomotion evolution for modular snake-like robot are executed in Webots environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.311-317
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• 2010

In the paper, we propose an improved mobility method of modular robots by physical docking in the uneven environments. The modular robot system consists of autonomous docking device, 3 DOF robotic arm, motion controller, and main controller. Real-time location and direction of the robot are estimated using inner GPS and they are used to control direction and path of each robot for physical docking between modular robots. We design a navigation algorithm of modular robot using physical docking and cooperative navigation in the environment with broken road and low stair. The proposed method is verified by navigation experiments of three developed modular robots in the uneven environments.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.11
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• pp.1272-1278
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• 2011

Mechanisms of the robot system should be developed according to the task. In this study, we propose improving adaptability of the robot mechanism with the modularized joint mechanism. Adaptability is the measure of the system ability to cope with change or uncertainty. Modular type joint has been widely used in development of various robots including reconfigurable robots. To build robotic systems more flexibly and quickly with low costs of manufacturing and maintenance, we have designed a modular type joint with one degree of freedom for general purpose. This module is designed to be compact, light-weight and self-controlled. In this design, we consider the kinematics and dynamics properties of the modular type joint.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.270-276
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• 2016

This paper proposes a design methodology of self-reconfigurable kinematics and control engine for modular and reconfigurable robots. A modular manipulator has been proposed to meet the requirement of task adaptation in versatile needs for service and industrial robot area and the function of self-reconfiguration is required to extend the application of modular robots. Kinematic and dynamic contexts are extracted from the module and assembly information and related codes are automatically generated including controller. Thus a user can easily build and use a modular robot without professional knowledge. Simulation results are presented to verify the validity of the proposed method.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.9-14
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• 2004

Rational sense is affected by emotion. If we add the factor of estimated emotion by environment information into robots, we may get more intelligent and human-friendly robots. However, various sensory information and pattern classification are prescribed for robots to learn emotion so that the networks are suitable for the necessity of robots. Neural network has superior ability to extract character of system but neural network has defect of temporal cross talk and local minimum convergence. To solve the defects, many kinds of modular neural networks have been proposed because they divide a complex problem into simple several subproblems. The modular neural network, introduced by Jacobs and Jordan, shows an excellent ability of recomposition and recombination of complex work. On the other hand, the recurrent network acquires state representations and representations of state make the recurrent neural network suitable for diverse applications such as nonlinear prediction and modeling. In this paper, we applied recurrent network for the expert network in the modular neural network structure to learn data pattern based on emotional assessment. To show the performance of the proposed network, simulation of learning the environment and behavior pattern is proceeded with the real time implementation. The given problem is very complex and has too many cases to learn. The result will show the performance and good ability of the proposed network and will be compared with the result of other method, general modular neural network.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.79-85
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• 2006

This paper presents a strategy and tactic for robot soccer using furry logic mediator that determines robot action depending on the positions and the roles of adjacent two robots. Conventional Q-learning algorithm, where the number of states increases exponentially with the number of robots, is not suitable for a robot soccer system, because it needs so much calculation that processing cannot be accomplished in real time. A modular Q-teaming algorithm reduces a number of states by partitioning the concerned area, where mediator algorithm for cooperation of robots is used additionally. The proposed scheme implements the mediator algorithm among robots by fuzzy logic system, where simple fuzzy rules make the calculation easy and hence proper for robot soccer system. The simulation of MiroSot shows the feasibility of the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.2
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• pp.118-125
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• 2012

Based on recent advances in technology, many robots are developed and they are used in a hazardous environment such as military operation, fire, and building collapse and so on. Among them, reconnaissance robot should be able to perform various missions which people can not do. So it needs the capability of moving with hiding its position on rough terrain, overcoming obstacles, and guaranteeing its efficiency of reconnaissance. For this reason there are in progress of researching biomimetic robots. Therefore in this paper we proposed robot mechanism, two modules based on the screw and wheel mechanism which mimic snake, and the spiral climbing method was considered for overcoming the situation when moving on the trees.