To prevent the gap falling of object, robot hand need to cover with a flexible sensor to obtain the load, load position, and load direction apply to the robot hand. A newly sensor consists of hemispherical elastic model and a load measurement layer, which is composed of an upper substrate, a lower substrate, and an electric conductive material was developed. Increasing or decreasing the load on the electric conductive material causes its internal resistance to change, allowing the measured voltage change between the upper and lower electrodes to be used to calculate the load applied to the sensor. In this study focused on the normal load applied to the sensor, and the position of normal load applied to sensor was changed, the relationship between normal load, position of normal load and voltage change was investigated.

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Due to the characteristics of depth camera images captured by the Kinect's depth camera, the conventional calibration board can't be used and the conventional calibration method can't detect the predefined pattern on the calibration board. In this paper, we propose a novel calibration board for the Microsoft Kinect and a novel automatic camera calibration method for a RGB camera and a depth camera equipped with the Kinect. Through experiment in real environment, we confirm the validity of our calibration board and method.

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Visual Servoing researches for hand-eye configuration having been presented so far seem to be vulnerable for tracking ability since it may lose a moving target. Our proposal to solve this problem is that the controller for visual servoing of the hand and the eye-vergence should be separated independently based on decoupling the motions each other. Base on this prerequisite the eye-vergence system to track target object by camera to be in view sight can have higher trackability than conventional visual servoing with fixed cameras. We have confirmed this superiority of eye-vergence system through frequency response visual servoing experiments with full 3-D pose tracking.

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In this research, we propose a low-cost 3D laser scanner for civil engineering and construction fields using robot technology. This system consists of a low-cost 2D laser scanner, a rotating table and an actuator, a total station, an automatic level, a tripod, and several corner mirrors. By rotating the 2D laser scanner which is detachable from the total station and the tripod around a vertical axis, 3D range information can be acquired at arbitrary positions owing to its portability. Scanning positions are precisely identified with the total station in a same manner with a geographical surveying. Thus this system is easy to use for workers who are used to dealing with surveying instruments. This paper reports some experimental results carried out in vast garden.

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A Laser scanner obtains a range value from the sensor toward the target by measuring the round-trip time of a laser pulse. At the same time, the reflectivity, which is the strength of the reflected light, can be acquired as a by-product of range information. Utilizing the reflectivity, we propose a new colorization technique for 3D models obtained by laser scanners. Pictures and reflectance images have similarities in their appearances. Focusing on that, we colorize a monochrome reflectance image utilizing the analogy to a color picture taken for the same scene, and then create a colorized 3D model by mapping color information to it corresponding to the reflectance image.

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This paper proposes a new radar tracking filter called Noise-estimate Particle Filter (NPF) which combines kalman and particle filters. The tracking performance of the kalman filter depends on the setting of several parameters such as a system noise and an observation noise. However, it is quite difficult to choose proper parameters for various scenarios beforehand, and thus they are regulated in trial-and-error manner in some cases. The proposed filter estimates proper noise parameters of a kalman filter based on a scheme of a particle filter on-line. Simulation results show that the proposed technique has a higher tracking performance in various scenarios than conventional kalman and particle filters.

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This paper proposes a method Visual SLAM using 6 DOF accelerometer. Each measured data is integrated by the extended kalman filter (EKF). Evaluation of the proposed method is done by the experiments on a simulation environment. The evaluation results show the effectiveness of the proposed method.

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The purpose of this research is development of a tactile sensing system including self-reference and bidirectionally of human tactile perception. We have developed a finger-mounted skin vibration sensor using accelerometers. It does not interfere in contact of object and skin and it measures skin vibration in active touch. In this paper, influence of contact pressure and contact area on skin vibration characteristic is investigated.

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In this paper, a measurement method of incipient slip is proposed for human grasping motion analysis. A measurement system which has a built-in camera and a built-in omnidirectional mirror, is used to capture palm images during grasping motion. The incipient slip distribution is analyzed in some experimental conditions which are different weight and different cylinder size. Experimental results show that the incipient slip distribution has a bias. We discuss about the relationship between the bias of the incipient slip distribution and the somatic characteristics.

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This paper proposes a vibrotactile glove interface that enables a user to perceive tactile information of virtual object. We also evaluate mental imagery provided from vibrotactile stimuli using the proposed interface. The vibrotactile interface is required to be simple to use, has a high portability and be light. We therefore propose a glove-type vibrotactile interface. In addition, active touch might be useful to realize informative tactile communication. To provide tactile stimuli based on movement of the fingers, five bending sensors are installed on the glove. In this paper, we investigate tactile mental imagery of users caused by vibration to design vibration stimuli. After that, we apply the vibration stimuli model to active touch. We evaluate tactile mental imagery of users in both cases of passive touch and active touch.

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In this study, we report on a palpation device with a roller to detect a solid object in a flexible object. This palpation device consists of the roller, a shaft, a spring, a case, a top plate, and a force sensor. This device scans the surface of the flexible object in which the solid object was embedded. This device measures reaction force by several shapes of the measurement objects. Since the roller reduces the friction, the device scans easily. The difference of the reaction force increases with decreasing depth. Moreover, the shape of the reaction force graph is similar to the upper surface of the solid object. We were able to detect quantitatively the solid object in the flexible object by our palpation device.

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A novel tactile sensor using Giant Magnetic Resistive (GMR) elements and a permanent magnet have been proposed in our previous study. The output voltage of GMR elements depend on magnetic flux density of a permanent magnet. The proposed has difficulty in measuring three-axis displacement of (Δx, Δy, Δz) when the magnet is rotating. In this paper, we propose the formulation which can measure displacement of (Δx, Δy, Δz) and also two rotation angle of (Φx, Φz) of a permanent magnet. We calculate the displacement vector using the regression analysis of the magnetic field which has analyzed preliminarily. Numerical results showed a good agreement with theoretical displacement of (Δx, Δy, Δz, Φx, Φz).

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This paper describes an attitude determination technique for small UAVs (Unmanned Aerial Vehicles). Small UAVs are attracted the attention for effective means of the collecting aerial information. However, there are few practical applications, because the accurate attitude data cannot be obtained due to its small payloads. We propose the attitude determination technique using the multiple single frequency GPS receivers. We install three GPS antennas on the wing of the UAV. We resolve the integer ambiguity of the carrier frequency of GPS observation data using the geometric constrain of the antennas to estimate the attitude of the UAV. In the result of the static test, we conclude the proposed method is effective to estimate the attitude for the small UAV.

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Measuring three dimensions position of thehornless object such as a cylinder with stereo cameras has a problem that corresponding misses occurred by round edge. This paper presents proposition to reduce the measuring error occurred by round edge. Chapter 1 describe round edge error. In chapter 2, Quantitative round edge error is measured by measuring 9 radius cylindrical objects. In chapter 3, changing cameras arrangement parallel to edge of object, round edge error reduces 50 percent.

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The authors aim to make 3-D map in rooms filled with smoke by removing smoke effects. Because the laser scanner is able to measure the shape of the smoke, the smoke is show up in the generated 3-D map. This paper attempts to recognize the smoke using laser reflection intensity, remove the smoke from the 3-D map, and correct the measuring distance if the laser measures 3-D shape of the smoke. The 3-D point cloud is divided into voxels. Smoke is characterized with an eigenvalue and laser reflection intensity in each voxel. In addition, the 3-dimensional shape warped by smoke effects is corrected both distance and angle of incidence.

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The authors aim at constructing a three-dimensional map by rescue dogs. Rescue dogs can search large scaled disaster sites quickly, because of its keen nose and its high physical ability. To construct a three-dimensional map, it is necessary to measure the position and posture of the dog. The authors propose a dog motion estimation method using Inertial Measurement Unit(IMU) and Global Positioning System(GPS). It is hard to measure the dog motions because the measuring devices cannot be directly fixed on the dogs. In addition, it is necessary to consider the balance of the measuring devices because the weight prevents the dog's motion. Therefore, the authors arrange the layout of the measuring devices on the dog's vest. We evaluated the measurement system by the experiments of the dog walks and runs. We also estimated the velocity and posture from the sensor information obtained from the measurement system.

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Sensing devices for intelligent tire that can measure the friction coefficient of a road surface are actively researched so as to improve the performance of vehicle motion control systems such as ABS (anti-lock braking system). Most of previous proposed devices, however, need complicated systems and have not been put to practical use. This study proposed a simple tactile sensor for an intelligent tire and established a method determining the value of the vertical load and frictional force that acting on the tire from the sensing results. Furthermore, the prototype tactile sensor was fabricated and its availability was confirmed.

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This paper proposes a method for evaluating a softness tactile display using a photoelastic tactile sensor. The developed tactile sensor can measure contact pressure distributions(CPDs) on both real samples and a softness tactile display, thus enabling calibration of display parameters through comparison among measured CPDs. The tactile sensor is made of transparent resin that is covered with a thin sheet with projections aligned at a regular interval of 2 mm. A digital camera, together with polarizers, measures photoelastic light intensity through the transparent resin. The acquired images are processed by offline image processing program to obtain CPDs. This work applies the sensor system to calibrate a softness tactile display with two control parameters. The sensor measures CPDs on the display by varying two parameters, and then the best parameter set that matches the real sample was explored by the least square method.

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This paper describes numerical simulations of a moving virtual robot. The virtual robot moves on a two-dimensional plane by the law based on the Newton's equations. The motion of the virtual robot is controlled by an artificial neural network (ANN). In order to control the virtual robot moving for a given target place, parameters of ANNs are optimized by particle swarm optimization (PSO). This type of control and learning method is called evolutionary ANN (EANN). It is shown by many numerical simulations that difficulties of learning rely on a position at which the target is placed. The phenomena is also found that a generalization ability of an ANN, that is, the ability to go toward not learned targets, decreases as learning of EANN progresses. Additional simulations show that learning simultaneously for two of more target places brings the high generalization ability.

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This paper presents the development of model robot based on multi agent system. We have proposed kinematics computing framework for flexible robot control using multi agent system (MAS). An agent consists of two elements, a joint mechanism and a control unit. It can compute owns kinematics solution by networking between the agents and transmitting to information on robot motion that analyzed by direct kinematics and inverse kinematics in each agent. This system's validity has confirmed by only simulation. So the purpose of this paper is to development of model robot and to verify the proposed kinematics computing framework using MAS. This paper deals with a development of simulator with LabVIEW and a design method to communication between the agents.

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In this study, we focus on reinforcement learning as a method of acquiring a robot's motion autonomously and with adjustment to the environment. To acquire various motions with the learning method, we suggested a method of learning to gain new motion by combining one motion with another. In the experiment, we applied control regulation with this method of learning to the robot; then, after the robot learned both moving-forward and turning motions, we had the robot acquire motion to go straight in the target direction. As a result, the robot learned the new motion, and at the same time improved the other two motions.

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This study deals with automatic generation of Post-Processors for generating instruction codes of multi-axis machine such as machine tools, robot manipulators, and so on, by applying the Inverse Kinematics calculation method based on MAS. The Inverse Kinematics calculation consists of autonomous agents which correspond to parts of machines. Those agents calculate individually states of themselves based on communications with each other, to make target states of end-effectors. Post Processors are generated as combining agent programs according to structures of multi-axis machines. This report describes a summary of the proposed system which is Post-Processor automatic generation, and estimation of trajectory accuracy of generated Post-Processors comparing with solutions by using pseudo-inverse matrix.

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We proposed a non-contact and simple method for measuring the diameter and the inclination angle of slender deep hole in castings such as cylinder block for automotive products. To measure the distance to the measurement surface, three laser beams are radiated perpendicularly from the sensing probe. Then the scattered lights are led to a prism and an image conduit in the probe and finally focused on CCD sensor. As the result of experiment, we confirmed to be able to measure the diameter with a high degree of accuracy even if the sensing probe is eccentrically located.

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In the previous paper, we used a semiconductor laser and a position sensing detector(PSD) to measure two DOF position of spherical ultrasonic motor(SUSM) and the effectiveness was confirmed. However, we have not realized three DOF position detection and control. Therefore, in this paper, we develop a new spherical rotor with two built-in semiconductor lasers to measure three DOF position of SUSM. Experiments are examined and the precision of the system is investigated.

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In this paper, we describe about a developed navigation system that supports the independent walking of the visually impaired in the indoor space. This system is composed of colored navigation lines, RFID tags and an intelligent white cane. In our system, some colored marking tapes are set on along the walking route. Theses lines are called navigation line. And also RFID tags are set on this line at each landmark point. The intelligent white cane can sense a color of navigation line and receives tag information. In our previous system, it is difficult to detect the direction of a user. Therefore, we developed a new system which can defect user's direction, we will report about this new navigation system.

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EMG measured the skin surface is widely used as an information source to determine various types of body movements. And there are many research results that use forearm EMG to detect hand motions. However most of them only can detect hand motions and cannot detect muscle power for each motion. In our EMG system, we suppose that muscle power is proportional to the amplitude of EMG. The power is estimated and the grip power of a robot hand is able to be controlled using estimated muscle power in our system. In addition, To perform a more precise control can be considered to build a closed loop feedback system as an object to a subject to pressure from the edge of hand. In this study, we developed a system to detect the pressure applied from the object was grasped by the grip force control of robot hand using EMG

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Our objective of this research is the development of methods that can be able to establish BCI using EEG that is measured using surface electrodes. BCI is a direct communication pathway between a human or animal brain and an external device. In this time, I developed a method to choose the EEG to control it. So, I will report on this.

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Until today, any analytical way to optimize a dynamic motion of a humanoid has not been established. Motion learning is an effective way to solve the problem and many works on it have been reported. However, in the past works, evaluation functions of motion were dependent on motions and made by human for each motion. To solve the problem, we propose to use mechanical energy as an evaluation function in learning of whole body dynamic motions of a humanoid. This paper indicates the possibility that mechanical energy could become a multipurpose evaluation function in learning of whole body dynamic motions of a humanoid for optimizing plural motions.

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This paper describes realization of a method to construct a learning control system which accepts many types of control targets. In addition, this learning control system can achieve a task that has a complex relationship between the controlled variable and the manipulated variable. By realization of this method, we can expect that robots will be able to perform more tasks and, we can apply this method to soft robots. This learning control system is composed by a backpropagation neural network, and is made by learning based on training data obtained by direct teaching from a human. By using this method, we tried to control the 3D position of the hand and angular speed of a windmill by the musculoskeletal humanoid Kotaro.

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In order to communicate smoothly among human, it is need to carefully consider many varieties of mental factors each other. There is the same situation in case of communicating between human and communication robots. In this study therefore, we try to develop a new mutual communication mechanisms considering mental factors such as tiredness, fatigue, exhaustion or boring. We also define an interesting degree of human to represent a strength value of interests. For this purpose, we discuss some aspects from the viewpoint of information theory. Experimental results about tiredness carried out based on the interactive word chain game between human and a communication robot are describe.

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A purpose of our study building automatic composing system. The system learns musical schema from existing music, then automatically composes a different music with similar feature by using learned schema. In this paper evaluation unit in the automatic composing system is proposed. This evaluate unit evaluates a melody generated from the other generation unit by using melody time-series prediction.

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In this study, we treat the cooperative agents systems in which there are multiple autonomous mobile robots, and the 3-Dimensional balancing problem is given. This problem is an example of corresponding tasks to find the appropriate movements for multiple mobile robots. Each robot agent on a flat board keeps being balanced state by using evolutionary robotics approach. The behaviors of mobile robots are calculated by corresponding neuro-controller which consists of artificial neural networks. Particle swarm optimization method is applied to evolve weight values of the neuro-controller. Numerical simulations are carried out by a simulator constructed based on 3-D physical engine PhysX. As a result of simulations, usefulness of our approach is clarified.

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Many studies have been done on autonomous locomotion robots based on physics modeling. However, most of them concern on walking and swimming locomotion and there are few studies of walking locomotion on an irregular ground. In this study, we focus on the autonomous behavior of animal walking locomotion on an uphill road and the downhill road. We applied Genetic Algorithm (GA) and Artificial Neural Network (ANN) to acquire the animal's autonomous behavior on the irregular ground based on physics modeling and verified that a suitable behavior can be acquired through numerical experiments.

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Recent years, the bioimaging using near-infrared (NIR) over 1000 nm wavelength is attracting attention. By using NIR, it is possible to observe arteries and veins under the skin. Because, NIR has high penetrating into a living body. Existed endoscope using Si-CCD camera can't capture over 1000 nm wavelength. There is Indium Gallium Arsenide (InGaAs) camera capturing NIR light, but it is still so large that can't be downsized for mounting endoscope. In this study, we propose Head-Scanning Mechanism consisted of MEMS mirror and photodetector for endoscope in place of Si-CCD camera and test image scanning by NIR. The experimental results suggest that the proposed method is useful for observe of in vivo deeply.

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The purpose of this study is to develop a diagnostic support system for anomaly detection from pathology image using HLAC features and SVM. In this paper, the optimization results of three parameters, which are image size of subspace to extract HLAC features, number of learning data, and kernel function for SVM, are reported. The optimal parameters are calculated by compare the correct detection rate of the proposed method with the diagnosis by a pathologist. The experimental results show that the correct detection rate depends on image size of subspace to extract features and number of learning data, the correct detection rate of anomaly cells decreases with an increase of the learning data, and the correct detection rate of normal cells increases with an increase of the learning data.

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Objective of this study is development of a BCI (Brain Computer Interface) system using noninvasive EEG (Electroencephalogram) that is measured from the scalp. In this paper, we described about an our developed EEG measurement system and measured ERP (Event Related Potential) by using this system. From results of experiments, we think that our system will be useful for the study of developing noninvasive BCI system.

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Objective of this study is development of a BCI (Brain Computer interface) system using noninvasive EEG (Electroencephalogram) that is measured from the scalp. As background research, the number of disabled persons in the country exceeded 3.5 million at the time of 2008. the number mentioned that increasing tendency. Especially, impaired limbs close to 50 percent and about 1.7 million people. In this paper, We described about an our developed EEG measurement system, measured EEG of holding right hand by using this system and analyzed in order to find the features. From results of experiments, I think that our system will be useful for the study of developing noninvasive BCI system.

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EMG measured from the skin surface is widely used as an information source to determine various types of body movements and there are many research results using forearm EMG to detect hand motions. In this filed, detected results are used in order to control some equipments like as an artifical hand. However most of them only can detect hand motions and cannot detect musucle power for each motion. If the power that is generated from musucle is able to be estimated by measured EMG, estimated results will be useful to control equipments. In this paper, we talk about our developed method that can estimate muscle power of pronation of hand and movement outside times of hand.

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Designing complicated behavior for an autonomous robot is a significant challenge in the field of adaptive behavior researches. We have proposed the behavior design method for virtual autonomous robots. It aims to obtain complicated behaviors by combining several artificial neural networks as primitive controllers. We have shown that the proposed method is capable of designing behaviors to achieve complicated tasks. This paper aims to introduce the multi-objective optimization into the proposed method to sustain diversity of primitive controllers. We conduct a simulation experiment for khepera-like mobile robot to acquire locomotion. Simulation experiments are carried out to show the effectiveness of our method.

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A morphology of an artificial creature plays an important role in its behavior artificial creatures because the acquired behaviors strongly are affected with its morphology. In this study, we simulate several type of artificial creatures with the different number of joints to acquire behaviors. Results are discussed on a relation between a morphology of the artificial creature and an acquired behavior in considering energy efficiency.

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This paper proposes how to acquire the composite behavior composed of the jumping, landing and walking behavior on artificial creature like a locust under the physical virtual environment. We acquires such behaviors by use of neuroevolution. Neuroevolution is one of the learning algorithm composed of artificial neural network(ANN) and real-coded genetic algorithm (RCGA) and we acquire optimized behavior of the locust model by use of it. In this study, we realize the jumping behavior first. After that, we realize the landing behavior to fix the posture of the locust model. Finally, we realize the walking behavior. We analyze the obtained behavior.

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This study verifies a relationship between environment and virtual seaweed to examine twining of seaweed in a cultivation pool. The morphology of virtual seaweed is modeled by L-system. Physics modeling is adopted to realize its physical motion. Two physical properties, adhesiveness, and tear are artificially introduced into this model. A virtual underwater environment is constructed by the Lattice Boltzmann method The virtual seaweed behavior is simulated in the given environment by physics calculation. In order to examine a force by alteration of water flow for the virtual seaweed, the simulation is executed under some water flow patterns. We ascertained that the twining of virtual seaweed has the close relationship with the water flow.

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This study aims to actualize the interactive behavior of virtual creatures with neural controller. For generating a control signal with a rhythmic pattern, a controller for the virtual creature is modeled by a combination of a Central Pattern Generator (CPG) and an Artificial Neural Network (ANN). The evolution of the behavior of the virtual creature is realized by a learning ANN and CPG An optimization algorithm is adopted into the learning process.

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The Job-shop Scheduling Problem is a classical, but yet modern problem. Because it belongs to the NP-hard problem and it is almost impossible to find out the exact solution, many heuristic methods have been proposed. Recently, Genetic Algorithm (GA), Local Clustering Organization (LCO) and so on have been proposed as a powerful tool to solve the problem. The optimal schedule becomes very important from a viewpoint of cost reduction in the manufacturing industry. This study optimizes the job-shop scheduling with multiple purpose functions by using evolutional computation. Numerical experiments verify that the evolutional computation obtains (quasi-) optimal schedule with multiple purpose functions.

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Generally, construction machineries are used in severe environment such as waste land and a mine. So, Fatigue of operator bring about delay of response and mistakes. Therefore, improvement of human fatigue bring prevention of their harmful effect and improvement of work efficiency. And then, evaluation that is able to compare human fatigue is required, so we inspected whether subjective evaluation and objective evaluation. So, we made the simple robot arm imitated a front of construction machinery, and evaluated human fatigue and work efficiency with vertical lever and horizontal lever. We used NASA-TLX, Flicker test and comparison of work efficiency for evaluation. From the experiment, we got the two results. The first, NASA-TLX and other evaluations method showed similar inclination. The second, horizontal lever had properties that is more efficient than vertical lever and besides larger physical fatigue in this experiment condition.

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In this paper, state transitions of primitive static states (PSS), which consist of 16 symbolic work states defined by using on-off state of the lever operations and joint loads for the manipulator and end-effector, are analyzed for describing work states in more detail. From a transition-condition analysis, practical state transitions (PST), which are frequent transitions in arbitrary construction work, are defined. PST can be classified into essential (EST) or nonessential state transitions (NST). EST extracts common phases of work progress and estimates positional relations between a manipulator and an object. NST reveals wasted movements that degrade the efficiency and quality of work. Work-analysis experiments using our instrumented setup were conducted. Results indicate that all the PSS definitely changes on the basis of PST under various work conditions, and EST and NST easily reveals work characteristics and untrained tasks related to wasted movements.

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This Paper describes development of high accuracy position making system using the mark robot and survey system. In the construction process of foundation works, the initial making on the base floor is very important work to set and built the construction materials exactly. However, the making errors were often reported by human error of marking worker. This trouble causes not only the lack of constriction confidence but also the decrease of work efficiency. In order to do high accuracy marking and to reduce the human errors, the automated marking system was developed using mark robot and the two survey instruments. In this mark robot, the marking device is installed at robot center and the error between mark point and stamp marker point can be modified exactly. Using this marking system, high accuracy marking can be executed. The marking process controlling in automation, the high efficient and accuracy foundation marking is performed.

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External wall inspection of the balcony surface of the apartment is difficult, because there is a necessity which guarantees with the privacy and security of the inhabitant. The inspector usually uses the temporary gondola, and inspects from outside the balcony surface of the apartment. In this research, we developed the external wall inspecting system which it can self-climb vertically on the balcony surface. This system is possible by gripping the projection of the balcony surface to move up-down the substance part, paralleling to the balcony surface. This system can examine the all tile of the external wall of building, and can acquire the image of the necessary points. In this paper, we describe the outline of this system and the efficiency which is obtained from the result of applying this system to the actual building.

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This paper describes the development of the high accuracy and low cost position measurement system using Laser Range Finder (LRF) and its application to the navigation system of pile driving machine in construction. To detect the machine position and rotation angle, the center of four cylindrical objects that were installed around machine was measured by LRF and the posture of machine was geometrically calculated from the relationships of distance between the objects. The centers of object were estimated by the maximum likelihood estimation method. In this paper, the algorithm of position measurement method for navigation system and its calculation process with cylindrical objects and LRF, and the application results of its navigation system were verified in constriction site.

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This paper discusses a 2-dimentional obstacle avoidance algorithm for mobile robots who search the environment obstacles by laser range finder. This algorithm finds the most obstacle free path that will allow a robot to move the furthest distance. In this algorithm, width of the robot is taken in to account when determining the obstacle free path for the robot. 2D laser range finder scans the horizontal data of the environment and algorithm finds the maximum travelable direction which covers span of 180° in front of the robot. The effectiveness of the algorithm is validated using MATLAB simulation framework using real environmental data captured by laser range finder.

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