It is considered that a person grasps an object efficiently by utilizing a critical force such that the object does not slip in the hand, and that regulation of the ‘grasp force’ based on slip information is useful for grasp control. Various slip sensors have been proposed for grasp control. Because many of the slip sensors and force sensors used in robots have analogue outputs, they are prone to being affected by electrical noise. Therefore they often require amplifiers, low pass filters and A-D converters. On the other hand, a force sensor using quartz resonators is robust to electrical noise since the output in this case is a frequency shift. This type of force sensor also has quick response time, high sensitivity, high resolution and wide bandwidth. Information on the grasp force, grasp position and slip and its direction is important for grasp control. Detection of grasp force and grasp position was reported in my previous paper. In this paper, a method of detecting slip and its direction by quartz resonators is reported. A principle for detecting slip and its direction, the results of changes in frictional force under various contact forces and slip speeds, and slip direction derived from two components of a frictional force are shown. It is demonstrated that an individual slip and its direction can be detected using quartz resonators, and that quartz resonators are useful in constructing a robot sensor.

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A micro-step reference has been developed by using an anisotropic etching of a (100) silicon wafer. As the etching process of the reference is dominated by the crystal orientation, it has a geometrically accurate profile compared with those manufactured by conventional mechanical tooling techniques. The reference has a multi-step cross section so that calibrations of surface profilers are easily performed in a small measurement length within the full dynamic range of the measurment instrument. Three fabrication methods are described-1) multi exposure-etching, 2) stripe pattern modulation, and newly proposed 3) checker pattern modulation. A theoretical design and results of experimental fabrications are shown. All methods can be used for micro-step reference, however, the latter two have still some problems to be improved.

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In this paper, a design method of the nonlinear H_∞ state feedback is proposed for a nonlinear descriptor model of an inverted pendulum system. First, the nonlinear descriptor model of a polynominal type with structural uncertainties for the inverted pendulum system introduced. The descriptor variables of this model include not only state variables but also the time derivative of state variables. Next, a state-dependent matrix inequality condition, which is can be transferred to the finite number of linear matrix inequalities, for the nonlinear robust H_∞ control problem and the eigenvalue location problem is given. The validity of the proposed nonlinear H_∞ control is shown through experiments as compared with the other nonlinear H_∞ control.

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This paper discusses potential and stable region problems in feature-based visual servoing. Visual servoing controllers proposed so far are valid only for the features in the neighborhood of the reference features. For initial features far from the reference may converge to a feature set that is different from the reference. Even worse, for some special cases the camera moves away from the reference position. In this paper, the visual servoing is considered as a potential minimization problem whose potential being squared error of the features. Stable region is visualized by using the potential and artificial potential switching control is proposed to enlarge the stable region.

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In order to build gymnastic robots and jumping robots, we have derived the complete analytical solution to the posture control problem of a two-link free flying object with initial angular momentum. We have shown that the problem becomes singular when initial body angle is far from the reference point and derived formulae to calculate the optimal switching condition, optimal terminal time and optimal trajectories. As an application, the high diving motion is simulated.

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In this paper, a learning algorithm is constructed for variable hierarchical structure learning automata with P-model stationary random environments at each level. The learning property of our algorithm is considered theoretically, and it is proved that the probability finding the optimal objective path can be approached 1 as much as possible by using our algorithm. In numerical simulation, the usefulness of our algorithm is shown.

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This paper deals with a merging control of vehicles with inter-vehicle communications, which would greatly contribute to increase safety and decrease traffic congestion. Algorithms for merging control of vehicles using a concept of a virtual vehicle and for inter-vehicle communications for the control of platoons are presented. A virtual vehicle is generated by mapping a vehicle on a lane into another lane, in order to enable longitudinal control between vehicles to make smooth merging. The inter-vehicle communications are needed to make a virtual vehicle before merging and to control vehicles during merging. The inter-vehicle communications consist of inter-platoon communications and intra-platoon communications. An algorithm of intra-platoon communications using ring-network is presented. The results of a simulation study and an indoor experiment show the feasibility of the merging control using the inter-vehicle communications.

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This paper studies grounding of humans' teaching information by a mobile robot. Human and robot have different sensors and actuators. It is difficult for the robot to understand humans' words that are indirect sensory information for the robot. This paper proposes an autonomous robot system that can ground the humans' teaching information. This system acts in an environment using the action rules given by a human, and collects data from its own sensors and actuators. Learning with the collected data using Genetic Algorithm (GA) and a Fuzzy-Neural Network (FNN) is done. The robot acquires new action rules based on its own sensors. This acquisition is called grounding of teaching information in this paper. The effects of the proposed system are shown with simulation results.

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One of the major problems of the technique that controls actions of agents by potential functions is to determine the function shapes suitable for the environment. In this paper, we study multi-agent environment where each agent autonomously acquires the parameters of potential functions. Actions of an agent are restricted by a gradient of scalar potential functions. We propose a method using reinforcement learning, especially classifier systems. Experiments with a pursuit game are done, and the following are confirmed: acquisition of the potential parameters for capturing the prey agent is possible; acquisition of the potential parameters for the two hunter agents to control each other and cooperatively capture the prey agent is also possible.

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In biological complex dynamics, a system should be discussed in terms of mutual interaction between subsystems. And where, there are conflicting two tendencies; one is adaptation to inputs from environment, while another is deviation from the inputs. To characterize these conflicting sidefaces of complex dynamics, theoretical framework of information flow rate is available. But this framework has limitation in analyzing subsystem which has large degree of freedom. In this paper, a new method to overcome this limitation is proposed, and generation and transmission of information in subsystems of coupled map lattice (CML) systems are estimated as an example.

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An estimation method for sensitivity of taste is developed by using linear second order system model. Also, the method is applied to the comparison of the sensitivity of taste between person of advanced age and young adult.

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This paper is concerned with quadratic stability of linear systems. The systems considered here have diagonally structured and Frobenius norm-bounded perturbations. An LMI-based quadratic stability condition for the systems is derived and a design method for the state feedback quadratic stabilizer is developed.

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In this paper, we consider an one-link flexible arm of length L. One end of the arm is attached to a motor shaft with the arm axis perpendicular to the motor shaft axis and the other end is attached by a payload. The main purpose of the controller design is the supression of the generation of oscillations during control of angular position. We propose in this paper, a eventual sliding-mode controller with a non-linear observer and confirm its effectiveness through experimental investigations.

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Several adaptive control algorithms for robot manipulators using artificial neural network (ANN) have been proposed and an algorithm using physical structure of robot manipulators also has been proposed. But the structure of ANN should be modified according to the change of the degree of freedom of the system. In this paper, we propose the algorithm in which structure of ANN is independent of the degree of freedom and its performance is compared to some other algorithms by simulation and experiment.

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