In order to easily realize the surface contact work, example as explorations and painting, etc., we proposed a PRY style 6-DOF manipulator, and a position, posture, force and moment hybrid control for the hand of it. Firstly, a Method of Sequential Retrieval was proposed for solving the inverse kinematics of the 6-DOF manipulator, even if the shafts of the upper 3 joints don't cross at the one point. And then, the position, posture, force and moment hybrid control was proposed by the expansion of conventional position and force hybrid control for dealing with the surface contact work. Furthermore, in order to avoid the calculation of the inverse Jacobian matrix, a Difference Inverse Kinematics Method was proposed. Finally, the purpose of this study was realized by the simulation using a CAD dynamic model.

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The representative method of controlling industrial robots is adapted by the feedback control. However, when high-speed operation is sometimes required at real time control, it is difficult to use the feedback control because of the reason why there is complexity of the motion of the equation. As one of the method how to solve this problems, the computed torque control which had the ability of the compensation for nonlinearity is tested for three links manipulator. Consequently, the calculated amount of the torque was used and succeeded the tracing for the simple circler orbit by the top of manipulator. But, total angle θ_T composed by the harmony of the angle of each joint should be constancy. From the our experimental results, it is expected for the practical use to simulate the motion of the manipulator. We are able to conclude the decision of the calculation method must be available for the non stationary θ_T in future.

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In this paper, the motion and vibration control system design for a flexible arm which possesses bending and torsional modes is dealt with. The position of center of the mass fluctuates due to an auxiliary mass connected to tip of the arm which denotes payload. This causes an uncertainty in bending and torsional modes. Three degree-of-freedom (DOF) reduced order model is identified according to Seto's procedure. Based on the obtained model, robust control design procedure utilizing H-infinity control theory is applied. In this study, the effect of low-pass filter on the steady-state and transient performances is investigated. Computer simulations are carried out and it is clarified that there exists trade-off property between steady-state and transient performances.

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This paper deals with robust control of a master-slave robotic system. We construct a master-slave system by using two 2-DOF robot manipulators and design a robust control system via impedance shaping and μ-Synthesis considering various uncertainties; e.g., environment and operator dynamics, perturbation of impedance model and time delay in telecommunications. The proposed control methodology can guarantee the robust stability and the robust performance for all these uncertainties of the master-slave system. Experimental results show the effectiveness of our proposed approach for various environmental uncertainties.

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This paper presents an active biped robot based on passive dynamic walking. In the first part of this paper, a Passive Dynamic Walker that achieves 3-D biped walking along a shallow down slope was presented. We then numerically analyzed an active biped robot which can walk straight on a flat level ground. Through the experiment of passive dynamic walking, it was shown that the rotational movement by using its circular foot bottom made a great contribution to the efficient walking. Because the rotational inertia is utilizable for walking, we installed actuators into knee joints to generate parametric excitation by using flexion of swinging legs. As a result, smooth biped walking on a level ground was realized according to this mechanism.

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This study aims at finding active biped robot designs with efficiency and simplicity of passive-dynamic walking. In this paper, it is shown that a biped robot with torso can walk efficiently on level ground over a wide range of speed by using torso and swing-leg control based on passive-dynamic walking. The torso and swing-leg control enable the biped robot on level ground to walk stably without gait planning. The torso is used to generate active power replacing gravity. The swing-leg control is applied in order to satisfy the transition condition of the swing leg and the stance leg before the robot falls down. It is also shown that the swing-leg control effects the efficiency of walking.

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It seems that the emergence of intelligence in an autonomous robot exists in the dexterity of human or creatures as complex systems and the research style and the development procedure along this approach should be necessary for realization of a real intelligent robot. This paper realized the simple self-sustained humanlike robust walking NANBA of humanoid biped robot GENBE based on distributed control of physical body in a martial art without ZMP control, which uses only small active power with simple chaotic limit cycle using gravity, further developing into autonomous walking.

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This study aims at establishing a new control strategy for more natural and efficient bipedal locomotion. In this study, the robot is modeled as a planar biped model composed of a torso, hips, and two different legs with knees, but without ankles. The proposed method consists of Central Pattern Generator (CPG) for legged locomotion and torso attitude control. It is well known that the CPG controller copes with environmental changes by mutual entrainment of the oscillatory activities of the CPG and the body. Therefore, the biped robot can walk on both a level ground and a slope, and has the robustness for environmental changes. Moreover, the torso attitude control is executed concurrently with CPG controller for legged locomotion in the method. By utilizing the interaction between torso and legs, the biped robot with the torso can walk on the level ground over a wide range of speed. This paper presents a systematic control design method of the proposed strategy by using the genetic algorithm. In order to verify the effectiveness of the proposed method, computational simulations were carried out. As a result, it was demonstrated that the biped robot can walk on the level ground at a variable pace according to the desired torso angle given as an external command. Moreover, it was confirmed that the proposed controller has the robustness for environmental changes and external disturbance, and the biped robot can walk naturally on the uphill and downhill slopes.

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This paper discusses creeping locomotion on unknown undulatory terrain by a snake-like robot capable of three dimensional (3D) motion. Continuum modeling is exploited to obtain a control law. Influence of the control parameters are examined by simulations modeled as closely as possible after a prototype robot with finite number of rigid links. The proposed method is demonstrated to be effective for the motion passing over a hump by experiment using the prototype.

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The mine detection hexapod robot COMET-III is driven by hydraulic power. Because of the strong nonlinear characteristic of the hydraulic system, conventional classic methods produce the delay to the trajectory. In the unknown environment of minefield, the robot leg must follow a trajectory correctly. The sliding mode control has strong robustness to parameter variation or disturbance, and the model following control make a real system follow the dynamic characteristics of a reference model. In this paper, we design a reference model following sliding mode controller, which combines the advantages of both control theory, and so improves control performance.

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In this paper, the method for changing control mode based on position and force errors is applied to a two-fingered robot hand composed of the elastic joints, and the validity of the method is verified. First, an instruction value strategy for grasping and transporting an unknown object by this robot hand is proposed. Next, the simulation model of the robot hand that is called "Chopsticks model" is constructed and the simulation of grasping and transportation control is performed by the application of the proposed instruction value strategy. Furthermore, the grasping and transportation control experiment is conducted by using the same robot hand as a simulation model made for trial purposes. Simulation results and experimental results illustrate the validity of the proposed method.

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The combined control method consists of Central Pattern Generator (CPG) for legged locomotion and torso attitude control has been proposed. The combined control has the adaptability to the change of environment with CPG. Moreover using the control method, it has been confirmed that walking speed is changed according to the desired angle of torso. Therefore based on the result, this study aims to propose the desired velocity tracking control of biped locomotion by changing the torso angle according to the difference between the walking speed and the desired speed. In this paper, computer simulations were carried out to verify the performance of velocity tracking. From the result, the effectiveness of this method was confirmed.

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Previous paper proposed SSM (sensor Steering Mechanism) for a laterally guided vehicle which follows the guideway. SSM realize high-speed moving on a straight line, but the cornering stability is influenced by the approach speed and the slip angle of tires. For the conventional SSM, the ratio of a sensor arm angle and a steering angle is 2 to 1, this paper discuses the steering ratio for speed-up at the corner. For the experiment, the steering ratio of the RR (Rear engine Rear drive) type SSM vehicle with 1kHz smart camera is changed to 1 to 1. Experimental and simulated results of running on the test track are compared.

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In this paper, for wheel robots equipped with articulated legs and conventional wheels, a tracking controller employing non-linearity between ground reaction forces and friction circles is proposed. An important feature of this controller is that both the position and the orientation of robot body and wheels have global and asymptotic stability to the desired values under mild condition. By this controller, robot can achieve both stabilization of balance and maximization of friction circles simultaneously.

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This paper presents a control strategy with neural networks for the all terrain vehicle robot during the development by the authors. This robot consists of two modules: a normal vehicle with wheels or tracks, and a controllable mass with parallel links to control the vehicle motion. Since it is not easy to control the parallel link mechanism with a feed forward controller, a neural network is employed and its effective learning is discussed through numerical simulations. Furthermore, the use of another neural network is proposed to determine the desired trajectory of the controllable mass. The desired position of the mass is also discussed with respect to falling moment of the vehicle.

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