In this research, EOG(Electrooculogram) signal was analyzed to predict the subject's intention using a fuzzy classifier. The fuzzy classifier is built automatically using the EOG data and evolutionary algorithms. An assistant robot manipulator in redundant configuration has been developed, which operates according to the EOG signal classification results. For automatic fuzzy model construction without any experts' knowledge, an evolutionary algorithm with the new representation scheme, design of adequate fitness function and evolutionary operators, is proposed. The proposed evolutionary algorithm can optimize the number of fuzzy rules, the number of fuzzy membership functions, parameter values for the each membership functions, and parameter values for the consequent parts. It is shown that the fuzzy classifier built by the proposed algorithm can classify the EOG data efficiently. Intelligent motion planner that consists of several neural networks are used for control of robot manipulator based upon EOG classification results.

The important issue of emotion recognition from speech is a feature extracting and pattern classification. Features should involve essential information for classifying the emotions. Feature selection is needed to decompose the components of speech and analyze the relation between features and emotions. Specially, a pitch of speech components includes much information for emotion. Accordingly, this paper searches the relation of emotion to features such as the sound loudness, pitch, etc. and classifies the emotions by using the statistic of the collecting data. This paper deals with the method of recognizing emotion from the sound. The most important emotional component of sound is a tone. Also, the inference ability of a brain takes part in the emotion recognition. This paper finds empirically the emotional components from the speech and experiment on the emotion recognition. This paper also proposes the recognition method using these emotional components and the transition probability.

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

This paper describes a sonic polygonal multiple reflection range sensor (SPMRS), which uses multiple reflection properties usually ignored in ultrasonic sensors as disturbances or noises. Targets such as a plane, corner, edge, or cylinder in indoor environments can easily be detected by the multiple reflection patterns obtained with a SPMRS system. Target classification and feature data extraction, such as distance and azimuth to the target, are computed simultaneously by considering the geometrical relationships between the detected targets, and finally the environment model is generated by refining the detected targets. In addition, the narrow field of view of a sonar range sensor is increased and the scanning time is reduced by active motion of the SPMRS stepping servomechanism.

This paper introduces the development of a range sensor based integrated navigation system for a multi-functional indoor service robot, called PSR (Public Service Robot System). The proposed navigation system includes hardware integration for sensors and actuators, the development of crucial navigation algorithms like mapping, localization, and path planning, and planning scheme such as error/fault handling. Major advantages of the proposed system are as follows: 1) A range sensor based generalized navigation system. 2) No need for the modification of environments. 3) Intelligent navigation-related components. 4) Framework supporting the selection of multiple behaviors and error/fault handling schemes. Experimental results are presented in order to show the feasibility of the proposed navigation system. The result of this research has been successfully applied to our three service robots in a variety of task domains including a delivery, a patrol, a guide, and a floor cleaning task.

In this paper, a new collision avoidance algorithm based on the dynamic model of a mobile robot is proposed. In order to avoid obstacles on the path of a mobile robot, intelligent force control is used to regulate accurate distance between a robot and an obstacle. Since uncertainties from robot and environment dynamics degrade the performance of a collision avoidance task, neural network is used to compensate for uncertainties so that the collision avoidance can be performed intelligently. Simulation studies are conducted to confirm the proposed collision avoidance tracking control algorithm.

Researches on mobile robots have been mainly focused on the autonomous navigation and a lot of interesting results have been published so far. Most of applications are, however, fancy, unpractical, and very expensive to be used for 'UN-expensive' purpose. Well-known soccer robot may be an example of unpractical application. Un-autonomous mobile robot has, however, potential for a lot of practical applications. Especially, tele-operation of the un-autonomous mobile robot may the central issue of research. Major research topics for the tele-operated un-autonomous mobile robot include development of a force reflecting joystick for tele-operation and development of a sophisticated algorithm for smooth tele-operation. A new concept named fuzzy command smoothing algorithm is proposed in this paper in order to provide smooth motion to a tele-operated mobile robot. It gives smooth motion command to the mobile robot from possibly abrupt quick turn motion command of the joystick using fuzzy logic. Simulation results verify the usefulness of the proposed algorithm.

In this paper, the framework for accelerating the development of personal robots is presented, which includes the technology such as modularization with its own processing and standardization open to the other developers. Its basic elements are Module-D(Module of DRP I) characterized functionally and VM-D(Virtual Machine of DRP I) arbitrating Module-Ds. They can suggest the effective ways for integrating various robotic components and interfacing among them. Based on this framework, we developed a fully modularized personal robot called DRP I(Dynamically Reconfigurable Personal robot). Its hardware components are easily attached to and detached from the whole system. In addition, each software of the components is functionally distributed. For the materialization of the proposed idea, we mainly focus on the dynamically reconfigurable feature of DRP I.

A small biped robot system is designed and implemented. The robot system consists of a mechanical robot body, a control system, a sensor system, and a user interface system. The robot has 12 dofs for two legs, 6 dofs for two arms, 2 dofs for a neck, so it has total 20 dofs to have dexterous motion capability. The implemented robot has the capability of performing intelligent actions such as playing soccer, resisting external forces, and walking on a slope terrain. In this paper, we focus on the robot's capability of playing soccer. The robot uses a color CCD camera attached on its head as a sensor for playing soccer. To make the robot play soccer with only one camera, an algorithm, which consists of searching, localization, and motion planning, is proposed and experimented. The results show that the robot can play soccer successfully in the given environments.

This paper proposes a method that minimizes the consumed energy by searching the optimal locations of the mass centers of links composing of a biped robot using Real-Coded Genetic Algorithm. Generally, in order to utilize optimization algorithms, the system model and design variables must be defined. Firstly, the proposed model is a 6-DOF biped robot composed of seven links, since many of the essential characteristics of the human walking motion can be captured with a seven-link planar biped walking in the saggital plane. Next, Fourth order polynomials are used for basis functions to approximate the walking gait. The coefficients of the fourth order polynomials are defined as design variables. In order to use the method generating the optimal gait trajectory by searching the locations of mass centers of links, three variables are added to the total number of design variables. Real-Coded GA is used for optimization algorithm by reason of many advantages. Simulations and the comparison of three methods to generate gait trajectories including the GCIPM were performed. They show that the proposed method can decrease the consumed energy remarkably and be applied during the design phase of a robot actually.

In this study, the performance of a heavy load pointing system has been investigated. The PI controller are being widely used in industrial application because of simple, cheap, and excellent performance. However, the requirement for control precision becomes higher and higher, as well as the plants becomes more and more complex. In order to achieve the satisfied control performance, we have to consider the affection of nonlinear factor contained in plant. In this paper, the neural-PI control law have been evaluated. The proposed controller is compared with the existing controllers through simulations, and the results show that the pointing accuracy of the proposed control system is improved against the disturbance induced by vehicle running on the bump course.

In this paper, It is studied to control and to monitor the remote system state using HTTP(Hyper Text Transfer Protocol) object communication. The remote control system is controlled by using a web browser or a application program. This system is organized by three different part depending on functionality-server part, client part, controller part. The java technology is used to composite the server part and the client part and C language is used for a controller. The server part is waiting for the request of client part and then the request is reached, the server part saves client data to the database and send a command set to the client part. The administrator can control the remote system just using a web browser. Remote part is worked by timer that is activated per 1 second. It gets the measurement data of the controller part, and then send the request to the server part and get a command set in the command repository of server part using the client ID. After interpreting the command set, the client part transfers the command set to the controller part. Controller part can be activated by the client part. If send command is transmitted by the client part, it sends sensor monitoring data to the client part and command set is transmitted then setting up the value of the controlled system.