We propose the elite saving strategy mode for combining a global search using GA with a local search which supplements the defect of a global search. In addition, we show the technique which executes the proposed algorithm two times for the detection of Go-board contour with more accuracy. We verified that the proposed algorithm detects the Go-board contour very well.

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In this paper the Intelligent Composite Motion Control, ICMC, is introduced as a method for evolutionary large-scale optimization, and it is described how adaptive large scale system optimization is achieved by the method in evolutionary manner. The ICMC is then applied to the shoot behavior realization problem in robot soccer to demonstrate the optimization process.

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We describe the research of biomimetic machines that has been founded at the advanced integration division of SICE. It is not the conventional bionics that fuses the bioengineering and the electronics, rather directs to the realization of a machine and a robot using several biomimetic technologies. We mainly discuss about biomimetic control, biomimetic perception, biomimetic robots and their applications.

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This paper presents a vision-related technique for 3-D position/orientation measurement. The proposed method utilizes the genetic algorithm (GA) and unprocessed gray-scale image input from stereo-vision, in order to perform recognition of a target being imaged with known target object shape

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This paper presents a method for a robotic ear based on the spatio-temporal gradient analysis with blind signal separation that estimates the object signals from overlapped signals. By using the spatial derivatives of mixed signals, not only the object source signals but also the arrival directions are estimated. The effectiveness of the proposed method is confirmed through the numerical experiment.

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The proposed system performs by integrated information with speech commands based on natural spoken language and images from a camera. The end-effecter of the robot is controlled to approach a desired object out of many objects. The present objective is to obtain a smoother cooperative interface system between human and robot, by coordinating speech and image information.

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Echo State Networks (ESNs) is a recurrent neural network. Finding a good one depends on choosing the right parameters for generation of the reservoir, intuition and luck. The proposed method eliminates the need for the tuning by hand by replacing it with a double evolutionary computation. First a broad search to find the right parameters. Then a search directly on the connectivity matrices fine-tunes the ESN. Both steps show improvements over other methods for an experimental dataset of underwater robot.

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Passive running gaits and their orbital stability of a planar one-legged robot are investigated by newly developed algorithm for detecting hybrid periodic orbits. Then, a novel “Energy-Preserving Controller” that produces interesting quasi-periodic orbits is introduced. Based on the recurrence, an additional adaptive controller similar to Delayed-Feedback Control for chaotic system is proposed. The controller achieves stabilization of “unknown” running gaits.

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This paper concerns a control specification which requires a finer description than the resolution which sensors and/or actuators inherently have. An experimental setup is taken to clarify our problem setup. The experimental setup is a ball position control. For the experimental setup, we propose a control algorithm based on discrete input and output and continuous state estimation. Finally, the proposed method is applied to the experimental setup to demonstrate its effectiveness.

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In an Internet-based control system, particular human operations may violate desired requirements. This paper extends the remote supervisory scheme in [5] to a modular one so as to reduce the supervisor synthesis complexity. Also, remote issued commands are guaranteed to meet specifications. A rapid thermal process in semiconductor manufacturing systems is provided to show the practicability of the proposed approach.

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A method for synthesizing feedback control logic for live and safe marked graphs has been given by Holloway and Krogh. The method strongly depends on the structure of marked graphs, and thus it has not been extended to wider classes. Structural characteristics of unfoldings are similar to that of marked graphs. Transforming a Petri net to an unfolding allows us to apply the Holloway’s approach to general bounded Petri nets.

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This paper is concerned with tracking control considering automatic detection of moving mold, as well as sloshing-suppression control in a self-transfer-type automatic pouring robot. This paper especially focuses on Reference Generator for detecting and tracking the moving mold.

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This paper presents a running and obstacle-navigation control principle for an inspection robot, and describes the development of control system based on a distributed expert system (DES) and electromagnetic shielding of control system. The inspection robot can run on the overhead ground wires and navigate obstacles autonomously, and inspect the damage of 500KV extra-high voltage power transmission line equipment.

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A new system is proposed for automatic transfer of the LNGC (Liquefied Natural Gas Carrier) membrane plasma welding-machine. It was realized by developing four movable legs with clamp and up/down modules. These legs support the body and the clamp module is implemented to attach the robot to the membrane plate. The proposed system has been evaluated by experiment.

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This paper is concerned with trajectory tracking and obstacle avoidance control using avoidance manipulability of redundant manipulators. In this presentation we define an evaluation method of the ability to avoid obstacle while tracking hand desired trajectory by evaluating the whole shape of redundant manipulator. And, we suggest a control system that the manipulator can keep avoidance ability high.

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This paper derives the learning curve of a polynomial kernel classifier in the asymptotic limit which linearly discriminates vectors nonlinearly mapped from input vectors. It is similar to but smaller than that of a linear dichotomy depending on the relationship between the subset in the feature space on which the mapped vectors lie and the true separating hyperplane.

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The associative memory can be regarded as a multiclass classification problem. Thus, we formulate it as optimization problems to maximize Hamming distances between each prototype and a separate hyper plane. To solve them, we propose some approximate optimization problems by using L1 or L2 norms. Moreover, we extend the proposed model into a nonlinear model which uses the kernel function. Through numerical experiments, we verified that the proposed model is effective in the storage capacity and the stability of stored prototypes.

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We propose a cost-aware method of detecting blood samples confused among different patients, using Self Organizing Maps. The map consists of a cluster reacting to confused data and that reacting to non-confused data. It is completed so that the latter cluster can become larger than the former, and allows reducing drastically the number of samples wrongly judged to be retested.

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In this paper, we propose new algorithm for the adjustment of the hidden units of RBFN based on Ant-based Clustering (AC). AC is an unsupervised cluster discrimination method which can estimate the number of clusters, but its performance is not always sufficient for some applications. We modified the original AC and applied it to the RBFN for human face detection.

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A biological binocular stereo vision processing was modeled based on Pulse-Coupled Neural Network(PCNN). Then disparity detection can be accomplished in the spontaneous synchronization of neurons corresponding to the correct matching points. Consequently, it is clarified that binocular stereo vision is generated through proposed model. Furthermore, our model is appropriate model based on actual visual processing of biology.

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This study demonstrates that NO signaling regulates adaptive behavior that is dependent on memory in insects. The results indicate that NO signaling must be an important factor of switching mechanism in the central nervous systems to evoke adaptive behaviors.

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This paper proposes a periodic motion pattern generation model inspired by biological brain motor systems. In the proposed model, the Brain part can recognize several kinds of environmental changes through its proprioceptive feedback time-series stem from own action, and also it can modulate its motion pattern by recalling well-suited CPG parameters with respect to the current Body dynamics.

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This paper discusses a fully decentralized algorithm able to control the morphology of a modular robot, consisting of many identical modules, according to the environment encountered. One of the significant features of our approach is that we explicitly exploit an emergent phenomenon stemming from the interaction between control and mechanical dynamics in order to control the morphology in real time.

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This paper describes a developed walking biped robot utilizing McKibben muscles and study on the influence of dynamic parameters on walking behaviors. A McKibben artificial muscle has suitable properties for realizing walking and running biped robot, but controlling McKibben muscles is difficult because of their nonlinearity. Therefore we design the dynamic parameters carefully.

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This research aims at finding the features that contribute to diagnose the illness as the malignant melanoma, based on color information of images. We divide RGB space into 4096 pieces and choose the spaces including colors peculiar to malignant melanoma. By using these spaces, about 26% of images of melanoma could be taken out only by color information.

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We propose a method to find differences among benign and malignant tumors, and gastric adenoma for helping pathologists diagnose gastric tumors objectively. We extract nucleus and cytoplasm region from tissue images, and calculate feature parameters of them by image processing. By evaluating distribution of feature parameters from discriminant analysis, we find out the objective feature parameters for diagnosis.

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This paper presents automatic detection for Dots. For the detection, we use closing operation, one of the morphological filters. But it has some faults to pick up Dots. That detects not only Dots but also edge of other structures. We improve the filter and compare it with classic one. An application of closing operation can solve problems.

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This paper proposes an algorithm of the contrast enhancement of the retinal fundus images using regional histograms. First we extract the background of the retinal area, then divide it into several regions according to their illuminations. Lastly, we adjust the illuminations in each region and enhance the image contrast. We show the effectiveness in extracting blood vessels.

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The test method for the flow-rate characteristics of a pneumatic component is specified in ISO 6358. When the flow-rate characteristics of a large pneumatic component are tested by this method, very large test equipment is necessary. In this study, a new test method that can measure the flow-rate characteristics of a pneumatic component by the small test equipment was developed.

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In this paper, the mechanism of a pressure differentiator, applying the principle of isothermal chamber and slit type laminar flow element, is explained. Then, the pressure differentiator is applied to the pressure control of an isolation table, as constituting a minor feed back, in order to compensate the non-linearity of a servo valve and realize an isolation table with higher gain and lower energy consumption.

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The differential pressure method is widely used nowadays for air leak detection. The air leak can be detected from the differential pressure occurs between the tested tank and a master tank, which is leak-tight. We have investigated how the unbalance of temperature recovery in the two tanks after air charge influence the differential pressure due to some factors.

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In this paper, we examined theoretically and experimentally the dynamic characteristics of a laminar flow sensor for gases which we developed. We evaluated the influence of inlet region and the linear characteristic. And we confirmed the flow sensor can be measured oscillatory flow up to 50[Hz] and the laminar flow sensor has phase-lead characteristic.

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We have developed a new thermal type micro flow sensor. We have achieved the sensor structure simple by introducing the constant-temperature operation. Prototype sensor sized 5 * 5 mm has been fabricated using MEMS technology. In the steady flow condition, the sensor has good linearity. To realize better dynamic characteristic, we have to analyze numerically and experimentally moreover.

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New configuration consisting of two pairs of exciting magnetic coils and a pair of signal pickup electrodes with the higher driving frequencies than those of conventional electro-magnetic flow meters is given. It brings the meters a function of self-calibration and lowers the condition of the fluid conductivity for the measurement. Theoretical analysis agrees well with experimental results and clarifies the feasibility.

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Full-electric control of hydro static transmission was studied through simulation. Transient responses of the system were examined. A two-degree-of-freedom control was applied to control of motor speed. It was demonstrated that control performance was improved under severe conditions.

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The Systems Sub-Theme in the Yaoyorozu Project has tried to develop a method for designing the ubiquitous information society. Scenario-based analysis is used for fostering socio-economic discussions and in-depth understanding among various specialized groups. The SYS ST has also developed modeling technologies related to these scenarios. This paper summarizes the future scenarios and technologies that the SYS ST has studied.

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The potential for new services in a ubiquitous computing environment has attracted much attention from both the business and technical perspectives. This paper provides an overview of the opportunities for providing new services and discusses the requirements of middleware technologies. During this year we have clarified user-centric requirements and have studied corresponding technologies from a trans-disciplinary science and technology viewpoint.

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In the near future the communication and computing devices will enable mass-market scale ubiquitous services and applications. The main challenge will be software that fulfils the needs of personalized, ambient-aware services and applications usable anywhere, anytime. A key enabler for this vision is personal networking supporting the communication in different kinds of environments.

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In this paper we show that the power of the Routh table goes much further beyond than merely the testing of the stability of polynomials. In particular, we show that the Routh table can actually lead to elementary solutions to many problems in advanced linear optimal and robust control.

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The generalized Kalman-Yakubovich-Popov (GKYP) lemma provides a unified LMI characterization of frequency domain inequalities in finite frequency ranges for both continuous and discrete-time systems. We developed a GKYP Design Toolbox which automatically generates the corresponding LMIs for controller synthesis problems with GKYP lemma. This paper explains the toolbox with design examples including controller reduction and pseudo-diagonalization for MIMO plants.

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We summarize an approach to robust and fault tolerant control proposed by the author. This design consists of two parts: a nominal performance controller and a robustness controller, and works in such way that when a component failure is detected, the controller is reconfigured by adding a robustness loop to compensate the fault. This is illustrated through a simple example.

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This paper establishes relationships between Bode type sensitivity and complementary sensitivity integral relations and optimal tracking and regulation performance, where the latter are defined in quadratic measures. These relationships link together frequency and time domain performance constraints, and further lead to new insight into these two independent areas of research.

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In Large scale disasters, it is very important to search for victims autonomously. Besides that, with information from robots, building good strategy is also very important. In our research, we do experiment on carbon dioxide sensor, checking for its ability to search for victims and propose some method aiding rescuer teams to build better strategy for searching victims

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This paper provides the method of detecting cracks in concrete pillars by using an acceleration pickup. By giving a shock on the pillar with a hammer, several types of stationary waves generated in the pillar are observed with the sensor on an edge of the pillar. The method identifies the location of the cracks by modeling the sensor output as an output of a linear dynamic system with unknown parameters and applying a Kalman filter and the maximum likelihood method.

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The friction force between a ballpoint pen and a paper has been directly measured. In the measurement method, the friction force is obtained by measuring the inertial force of a mass. A pneumatic linear bearing is used to obtain linear motion with negligible friction. The inertial force of the mass is obtained by accurately measuring the velocity of the mass.

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Developing a monitoring system in bathrooms is important to prevent the accidents. This paper proposes a new monitoring system by immersing a pipe with an acoustic sensor inside into the water. We can thus obtain not only direct sound information from the people, but also the water level information. For the water level, stationary waves inside the pipe are used.

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Various physical phenomena can be used to measure the powder level in a storage tank. This paper describes an accurate, novel and method employing acoustics to measure the amount of powder in a tank. The proposed method employs a probing pipe in a small loudspeaker. We catch a change of acoustic impedance of opening of a pipe. Change in acoustic impedance produce an output signal.

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This paper discusses the online estimation problem of frequency, amplitude and initial phase of a measured sinusoidal signal by using the adaptive method and filter theory. The proposed method is based on an identity between a sinusoidal signal and its second order derivative. The estimation errors converge to zero exponentially. Simulation results show the effectiveness of the proposed new method.

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An effective data fitter, which can restore the signal from the measurement results corrupted by noisy, together with its principle and analysis, are presented. Its application and results in the sensorless speed measurement of BLDC motors is also introduced.

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New time-domain SRC using Fourier interpolation to achieve less gate count than in frequency domain is proposed and implemented by FPGA. Layout area of the proposed SRC based on a 0.35um process is 5.728mm², smaller than the conventional SRC using filters. The noise level is reduced down to the quantization error level by using several improving methods.

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