• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.343-348
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• 2007

This paper presents an adaptive controller for the compensation of state-dependent disturbance with unknown amplitude in a digital servo motor system. The state-dependent disturbance is caused by friction and eccentricity between the wheel axis and the motor driver of a mobile robot servo system. The proposed control scheme guarantees an asymptotical stability for both the velocity and position regulation. An experimental result shows the effectiveness of the adaptive disturbance compensator for wheeled-mobile robot in a low velocity diffusion tracking. A comparative experimental study with a simple PI controller is presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.3
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• pp.245-249
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• 2012

In this paper, we propose a navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using an ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method is used to govern the robot motions. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.652-658
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• 2010

This paper presents the implementation and control of a two wheeled mobile robot(TWMR) based on a balancing mechanism. The TWMR is a mobile inverted pendulum structure that combines an inverted pendulum system and a mobile robot system with two arms instead of a rod. To improve robustness due to disturbances, the radial basis function (RBF) network is used to control an angle and a position at the same time. The reference compensation technique(RCT) is used as a neural control method. Experimental studies are conducted to demonstrate performance of neural network controllers. The robot are implemented with the remote control capability.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.70-75
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• 2003

There come various types of robot with researches for mobile robot. This paper introduces the multi-joint snake robot having 16 degree of freedom and composing of eight-axis. The biological snake robot uses the forward movement friction and the proposed artificial snake robot uses the un-powered wheel instead of the body of snake. To determine the enable joint angle of each joint, the controller inputs are considered such as color and distance using PC Camera and ultra-sonic sensor module, respectively. The movement method of snake robot is sequential moving from head to tail through body. The target for movement direction is decided by a certain article be displayed in the PC Camera. In moving toward that target, if there is any obstacle then the snake robot can avoid by itself. In this paper, we show the method of snake robot for tracing the target with experiment.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.64-69
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• 2010

In this paper, we propose remote navigation control for intelligent robot using particle swarm optimization(PSO). The proposed system consists of interfaces for intelligent robot navigation and user interface in order to control the intelligent robot remotely. And communication interfaces using TCP/IP socket is used. To do this, we first design the fuzzy navigation controller based on expert's knowledge for intelligent robot navigation. At this time, we use the PSO algorithm in order to identify the membership functions of fuzzy control rules. And then, we propose the remote system in order to navigate the robot remotely. Finally, we show the effectiveness and feasibility of the developed controller and remote system through some experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.161-166
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• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.335-340
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• 2011

In the study, a tangible interface using iPhone is proposed to control a mobile robot, instead of remote control by a joystick or buttons. The robot is controlled by iPhone like a handle bar, since acceleration sensors of iPhone are used in the proposed method. The sensors measure the angles changed on the xyz coordinates of iPhone. And their sensor values are stabilized by digital filters. Bluetooth is chosen for communication between a mobile robot and iPhone. In this paper, four type methods are considered and one of the methods is selected for remote control of a mobile robot. Experimental results show that the robot is easily and conveniently controled by the tangible interface based on iPhone.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.792-798
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• 2003

This paper is about implementation of intelligent robot based on home network. Existing robots are mainly stand alone type. Home network is spreading rapidly and can play an important role as a path for informations between appliances in home. Robot can be more intelligent and have versatile functions with a junction of home network. By distribution of tasks through home network, robot doesn't have to process every task. In addition, robot can access to appliances through network as appliances are added continuously. In the future, smart space in which robot behaves on various types of network is in expectation. In this research, home network based system which consists of home server, embedded robot, and intelligent robot is proposed and implemented.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1889-1892
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• 2002

In this paper, we propose the self-autonomous algorithm for mobile robot system (MRS). The proposed mobile robot system which is learned by learning with the neural network can trace the target at the same distances. The mobile robot can use ultrasonic sensors and calculate the distance between target and mobile robot. By teaming the setup distance, current distance and command velocity, the robot can do intelligent self-autonomous drive. We use the neural network and back-propagation algorithm as a tool of learning. As a result, we confirm the ability of tracing the target with proposed mobile robot.