Kae Doki

Study on modeling and recognition of human behaviors by If-Then-Rules with HMM

Conventional intelligent systems require humans to acquire knowledge and technique about the systems in order that humans receive their benefits. This means that humans must adapt to the systems. For this problem, it is necessary to realize such systems that can support humans, in other words, the systems that adapt to humans by considering human behaviors. In order to realize this idea, we propose a modeling and recognition method of human behaviors in this paper. In this method, we suppose that a human changes his behavior according to the change of the situation around him, and this concept is expressed by If-Then-Rules. In the rules, the change of the situation around a human is described by HMM(Hidden Markov Model) in order to consider its temporal and spatial redundancy. To recognize the change of human behaviors, the optimal If-Then-Rule is chosen based on the current human behavior and similarity to the time series data of the situation obtained by sensors. In this paper, human driving behaviors are considered as an example of human behaviors, and a recognition system of human driving behaviors is constructed. The usefulness of the proposed method is examined through some experimental results with the constructed system.

Motion analysis of a micro-actuator using three piezoelectric actuators

Displacement of a micro-actuator is described theoretically and experimentally. The actuator uses three stacked-type piezoelectric actuators which are connected in an equilateral triangle, and three electromagnets which are attached at all the vertexes of the triangle. The actuator, which can realize a precise motion, is developed for a flexible conveying system, such a desktop manufacturing system. The actuator is used in a micro/nano system which requires a nanometer resolution with multi degrees of freedom. The displacement of the actuator is simulated and demonstrated experimentally

Delta-type miniature robot using levitation mechanisms

We study miniature robots using piezo actuators. We proposed a levitating type miniature robot and a delta-type miniature robot using piezos and electromagnets. We thought that friction force control using levitation mechanism can realize more precise operation, and we proposed delta-type miniature robot using levitation mechanisms. This robot is combined the advantages of the two robots. This robot has three levitation mechanisms using the squeeze film effect. It can realize the linear and rotational displacement by its delta-type structure. Furthermore, its levitation mechanisms can help to decrease the frictional wear between the robot and working surface. In this study, we produce experimentally the L-type miniature robot using levitation mechanisms. This robot also can realize the linear and rotational displacement, and reduce a using piezo.

Modeling method of human actions based on the situation with variable level of the spatial-temporal abstraction

In order to realize a system that adapts to a person by considering human behaviors such as an automatic monitoring system and a driving support system, the system must have a certain model of human behaviors. Therefore, we have proposed a modeling method of human behavior based on the causality between a situation around a person and a human behavior. In order to model human behaviors appropriately depending on the problem where the proposed modeling method is applied, the spatial and temporal abstraction levels of human behaviors should be adjustable. In this paper, we propose a modeling method of human behaviors that can adjust the spatial and temporal abstraction levels of modeled human behaviors. In this method, the temporal and spatial abstraction levels of human behavior can be adjust independently, and the spatial and temporal adjustment parameters are introduced in the time series clustering process. The usefulness of the proposed method is examined through the experiment.

Estimation of next behavior and its timing based on human behavior model with time series signal

A new modeling method of human behaviors is proposed in this paper. In the proposed method, it is assumed that a person changes his behavior according to the change of the situation around him, and this concept is expressed by If-Then-Rules, which are called behavior rules. In behavior rules, a human behavior is described as a discrete event, and the change of the situation around a person is described by Hidden Markov Model (HMM) which models multi-dimensional time series sensing data. Moreover, and early estimation method of the next human behavior and the timing of its execution is proposed based on the proposed human behavior model. In this research, human operations of a radio controlled vehicle are modeled as an example of application of the proposed model. The usefulness of the proposed method is examined through experimental results of behavior estimation with the constructed behavior model.

Position based impedance control based on pressure distribution for wearable power assist robots

In this paper, a new impedance control method for wearable assist robots based 011 pressure distribution is proposed. Conventional power assist systems could not realize high power assist because they did not consider about the physical contacts between the user and robot. Also, these systems assisted only for simple joints such as knee, elbow, limb and so on. I11 order to achieve higher power assist lor multiple joints such as shoulder and waist, it is desirable to consider the contact condition directly instead of torque that was used in conventional methods. The authors propose a position based impedance control system using pressure distribution between the user and robot. By using a pseudo torque calculated by pressure distribution, the impedance controller can be expected to reduce the dangerous contact pressure efficiently. I11 this paper, power assist 011 the multiple joints are assumed: forward-backward bending movements of the upper half part of the body. A structure of the assist robot is determined based 011 analysis of human movements. By applying determined robot model 011 simulations, the proposed impedance control method is evaluated by comparing contact pressure to conventional methods.

Compensating Characteristics of a Series-Shunt Active Power Filter Considering Unbalanced Source Voltage and Unbalanced Load

Recently, the suppression of the harmonic component in the electric power system has become an important problem. In this paper, we analyze compensating characteristics of a series-shunt active power filter by simulation and experiment when source voltage or load current becomes unbalanced. The harmonic and unbalanced voltages are detected and compensated in a series active filter using dq0 transformation. The harmonic and unbalanced currents are detected and compensated in a shunt active filter using pq-theory. The results of analysis show that the THD of the compensated voltage is 1.0% by simulation and 8.3% by experiment. The THD of the compensated current is 3.0% by simulation and 7.2% by experiment. It is shown that the series-shunt active filter can compensate the voltage and the current simultaneously and it has excellent compensating characteristics even when unbalanced components occur in the electric power system.

A Precise Motion Measurement of a Miniature Robot Driven by the Deformation of Piezoelectric Actuators

We measure the motion of a miniature robot and the trajectories of three legs. The robot consists of three stacked-type piezoelectric actuators connected in an equilateral triangle. The three legs, which support the main body of the robot, are fixed at every vertex of the triangle. The input waveforms applied to the piezos are rectangle and sinusoidal waveforms. We discuss the motion of the miniature robot and the trajectories of the legs under the conditions that the miniature robot can rotate or not.

Self-position Estimation of Autonomous Mobile Robot with Size-variable Image Template

We propose a new image template generation method for the self-position estimation of an autonomous mobile robot. In the proposed method, an image template is generated with genetic algorithm. Then, in the process of the self-position estimation, the size of the image template can be varied in order to change the time for the self-position estimation according to the situation around the robot. Therefore, a suitable image template is searched by GA search as the size of the image is varied. The position of the robot is estimated by matching the input image at the current situation with the stored image templates which indicate certain positions. As a criterion of the template matching, the normalized correlation coefficient is applied. This method is sensitive to the position shift of the image. Therefore, in order to realize the robust self-position estimation for the position shift, the amount of the position shift between the image template and the input image is compensated before the template matching. The usefulness of the proposed method is shown through some experimental results

Control waveforms applied to piezo elements used in a miniature robot

We developed a miniature robot using piezoelectric elements (PZTs). The miniature robot utilized the expansion and contraction of the PZTs. We applied rectangle waveforms to the PZTs and realized the rotational displacement of the robot. The rotational displacement varied widely when we used the rectangle waveforms. Optimal control waveforms, which were applied to the PZTs, were not clear. In this paper, we describe the rotation of the miniature robot, which is driven by three types of control waveforms; triangle, rectangle, and sinusoidal waveforms. The sinusoidal and triangle waveforms are suitable for the rotation of the miniature robot under our experimental conditions.