A design is presented for acceptable handing motion of arm-robots utilizing a transfer function, that linearly transforms a synchronized trajectory to the hand movement of the receiver which is emotionally acceptable to human psychology. The transfer function is named the “Kansei” transfer function in this paper. Motions of robots that cooperatively support human should be emotionally acceptable for humans. To form such a movement, an effective method is for robots to make their motions gentle when taking care of humans. First, the human motion of handing an object to another human constrained to a sagittal plane is analyzed and its features are extracted. Then, the possibility of applying the clarified features to the handing motions of a robot is examined. It is found that the movement characteristic of the hander can be approximated by linearly transforming the movements of the receiver, that is, the relationship of the two movements can be expressed by a transfer function. The second order lag element with suitable parameters is sufficient to describe the relationship. The parameters of the transfer function are experimentally determined and the resulting transfer function is tested in a series of handing experiments with a human receiver. Handing motions that are acceptable by human receivers are realized by adjusting parameters in the transfer function.

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This paper presents a gesture recognition method extending Temporal Templates so that they can contain not only vertical and horizontal motion but also depth information obtained from a binocular stereopsis. The proposed method can discriminate gestures with depth motion. At first, a disparity image generated from stereo images is divided into several disparity stages and in each disparity stage, a grayscale feature image (Temporal Template) is created by assigning the intensity according to the frame number to the area where motion has been detected. Next, a gesture model is generated from learning feature images acquired in each disparity stage by SVM. A gesture is recognized by checking feature images generated from input stereo images against SVM model. Experimental results have shown the effectiveness of the proposed method for recognizing gestures with depth motion.

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The rotary crane is widely used for the transfer and discharge loads in harbors, building sites, and factories. These tasks involve many problems such as load sway, positioning, and obstacle and collision avoidance. Therefore, the development of a control system to support operator is strongly demanded.The purpose of this paper is to develop an operator support system in consideration of obstacle avoidance and sway suppression. The information of danger is transmitted to an operator by haptic control.In order to suppress load sway, the Hybrid Shape Approach is applied and a potential field was derived by an equation of diffusion at cylindrical polar coordinates to construct the algorithm of crane velocity restriction for haptic feedback.The effectiveness of the proposed system is shown by simulations and experiments.

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It is really interesting to know how a blood flow has an influence on tactile sensitivity during Iiurrian fingertip exploration over an environment. In this paper, we examine experimentally how the tactile sensitivity is influenced under the condition that the blood flow is interrupted compulsorily by pressing the base link of humian finger. Through experiments based on Weber's law, we found that the tactile sensitivity improves temporarily with the significance test of 0.1% when pressing a finger base link. Experimental results also show that thete exists a close relationship between the stiffness of fingertip and the tactile sensitivity.

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This paper is aimed at the observation of human rhythm production according to multi-modal inputs using cognitive psychological experiments. Participants simultaneously received visual and auditory signals with random or periodic time sequences. The task was to tap alternately in time with the visual or auditory target sequence while a distractor sequence was presented in the other modality. We used three sequence conditions: 1) random visual and random auditory sequences, 2) random visual and periodic auditory sequences, and 3) periodic visual and random auditory sequences. Results show that rhythm production is strongly attracted to auditory signals under all conditions. Visual signals, however, affect rhythm production only in condition 3). These results suggest that visual and auditory information serve different roles as sensory information in rhythm production.

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In this study, in order to evaluate the timing control mechanism in a dynamical complex environment, we propose a new experimental method which is able to control the complexity of the temporal structure of the environment and analyzes the response characteristics. The results show significant differences for the detection between below and above the threshold, against the complexity of the temporal structure. It is therefore suggested that the timing control mechanism is affected by cognition.

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This paper presents passive dynamic walking with elastic energy. We propose a new type of passive dynamic walking robot by adding elastic materials such as spring or rubber between a supporting leg and a swing leg of the robot

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In recently, study on skiing turn is researched from various viewpoints. And the mechanism of the skiing turn using the skiing robot is clarified now. However, those mechanical models derived by using the approximate expressions don't match to an alpine skiing turn. Therefore, to provide further details of theoretical consideration, the passive type skiing robot is developed. The influence on the skiing turn such as the position of gravitational center and the shape of skiing are examined by using this robot. In this paper, it reports on their experimental results.

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This paper presents a practical hand image instruction learning system for partner robots using an advanced selforganizing map“Transient-SOM”. The construction of the proposal system is designed with 4 layers: a feature map to classify input images, an action map to acquire correct actions using a reinforcement learning algorithm, a memory layer to preserve “Best Matching Unit (BMU)” after one instruction training is finished, and a feeling map to express robot's internal state during learning. Experiments using an entertainment robot, AIBO (ERS-7, Sony Co., 2003), showed high effectiveness of the proposed system.

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This paper proposes a new mechanism to measure mass of an object in microgravity. The proposed system consists of a variable stiffness mechanism and an actuator. The object is attached at the tip of a blade spring in the variable stiffness mechanism. The actuator swings the blade spring periodically and the length of the blade spring is controlled to satisfy the anti-resonance condition. The mass of the object is measured with the desired period of the swing and the length of the blade spring in the anti-resonance mode. Numerical simulations and experiments are executed to confirm the effectiveness of the proposed method.

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In this paper, three parameters of an object, which is inserted between a pair of piezoelectric ceramic transducers in the homogeneous medium, - a position, diameter, and relative permittivity, - are estimated. In our proposed method, time of flight is measured by each piezoelectric ceramic transducer, and capacitance between a pair of piezoelectric ceramic transducers is also measured by using each piezoelectric ceramic surface electrode. Therefore, the ultrasonic and electrical properties are simultaneously obtained by the proposed sensing method. In the experiment, a column was inserted between a pair of piezoelectric ceramic transducers which were arranged inside the cylindrical equipment filled with distilled water, and time of flight and capacitance were measured. Three kinds of columns- polyvinyl chloride (relative permittivity ε_s: 2.25), polyoxymethylene (ε_s: 3.5), and polyvinylidene fluoride (ε_s: 6.8)-, were prepared. In addition, three types of diameters- 30, 35, and 40mm-, each with column were used. The position of the column, diameter, and relative permittivity were estimated from time of flight and capacitance.

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This paper presents two sleep indices related with REM sleep and; awake and non-REM sleeps defined from the heart beat and body movement measured by the pneumatic method. The former is defined by the heart rate variability and latter is defined by channel capacity in the measurement of heartbeat, which is the degree of how the pulse wave measurement is corrupted with the body movement. These indices were compared with the occurrence rates of the delta-waves, spindle waves in the electroencephalogram and rapid eye movements measured by a polygraph and show the relationship with these bio-signals. The sleep stages estimated by using the indices were more accurate than those estimated by the conventional method based on the heart rate and body movement.

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In the general reinforcement learning, state transition probabilities are estimated by samples, and an optimal policy is obtained. This paper intends to obtain the optimal policy by constituting an appropriate state space for the samples because each state space leads to each optimal policy. This paper proposes the criterion that evaluates the performance and reliability of the optimal policies to decide which optimal policy should be selected. The performance and the reliability have trade-off relation. We define a compatibility optimal policy decision problem that minimizes the criterion. This study provides a general method to solve the problem, and shows an approximate method to reduce computational efforts. This study also gives a state space reduction problem and its solution. Moreover the proposed method enables to make the learning efficient on general condition in which an optimal policy is learned by increasing samples. Numerical simulations examine the effectiveness of the proposed methods.

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This paper addresses online modification of reference trajectories for multiple robots with collision avoidance. A smooth mapping dependent on distances between the robots has been proposed to coordinate collision-free motion from given reference trajectories. The trajectories generated by the mapping allow the robots to avoid collisions with each other, and are smooth enough to be tracked by the robots. Moreover, when the reference trajectories are separated from each other, the mapping is identical and the modified trajectories remain unchanged from the original ones. Although the existing method works well for collision avoidance, the modified trajectories often include unnecessary avoidance motion. A new method based on the existing one is proposed to improve the mapping to generate more natural trajectories by eliminating the unnecessary avoidance motion. The new mapping depends not only on the relative distances but also the relative angles between the robots. Finally, the effectiveness of the proposed method is demonstrated by a simulation for three mobile robots.

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This report focuses on developing a control algorithm for obstacle avoidance in automobile maneuvering. For the derivation, an optimal control problem is formulated as minimizing the longitudinal movement to avoid the collision. The optimal inputs are obtained through a simple map in a three dimensional space comprised of the vehicle velocities in the longitudinal and lateral directions, the distance to avoide and the force acting to the vehicle. The optimal force input is then shown to be expressed as the forces distributed to the four tires.

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A hybrid type of global optimization methods with hierarchical structures is presented. While an intensive search is performed locally on a bounded region given as a neighborhood of a trial local optimum in the lower level, the bounded region is searched diversely to find the best neighborhood in order to prepare a global optimum in the upper level. The diversification and the intensification are known as the search strategies of meta-heuristic methods. The presented method is characterized by the hierarchical combination of the diversification and the intensification, where particle swarm optimization (PSO) accompanied with local search method is used. The effectiveness of PSO is tested in searching the best neighborhood for the global optimum of the benchmarks including a mechanical design problem with integer variables.

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This paper presents a new decentralized fault diagnosis strategy for event-driven controlled systems such as Programmable Logic Controller (PLC). First of all, the controlled plant is divided into some subsystems and the time interval between observed successive two events in each subsystem is modeled as a random variable by Timed Markov Model. Second, the Bayesian Network, which represents the causal relationships among faults and observations in each subsystem, are introduced. By exploiting the Bayesian Network, the comutational burden for the diagnosis can be reduced. As a result, large scale diagnosis problems can be solved for practical situations. Finally, the usefulness of the proposed strategy is verified through some experimental results of an automatic transfer line.

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