A new type of humanoid robot arm which can coexist and be interactive with human beings are looked for. For the purpose of implementation of human smooth and fast movement to a pneumatic robot, the author used a humanoid robot arm with pneumatic agonist-antagonist actuators as endoskeletons which has control mechanism in the stiffness of each joint, and the controllability was experimentally discussed. Using Kitamori 's method to experimentally decide the control gains and using I-PD controller, three joints of the humanoid robot arm were experimentally controlled. The damping control algorithm was also adopted to the wrist joint, to modify the speed in accordance with the power. The results showed that the controllability to step-wise input was less than one degree in error to follow the target angles, and the time constant was less than one second. The simultaneous input of command to three joints was brought about the overshoot of about ten percent increase in error. The humanoid robot arm can generate the calligraphic motions, moving quickly at some times but slowly at other times, or particularly softly on some occasions but stiffly on other occasions at high accuracy.

The hand posture estimation system by searching a similar image from a vast database, such as our previous research, may cause the increase of processing time, and prevent realtime controlling of a robot. In this study, the authors proposed a new estimation method of human hand posture by rearranging a large-scale database with the Self-Organizing Map including self-reproduction and self-annihilation, which enables two-step searches of similar image with short period of processing time, within small errors, and without deviation of search time. The experimental results showed that our system exhibited good performance with high accuracy within processing time above 50 fps for each image input with a 2.8 GHz CPU PC.

The purpose of the study is to obtain the automatic and optimal matching between a motion-measurement device such as a data glove and an output device such as a dexterous robot hand, where there are many differences in the numbers of degree of freedom, sensor and actuator positions, and data format, by means of motion imitation by the humans. Through the algorithm proposed here, a system engineer or user need no labor of determining the values of gains and parameters to be used. In the system, a subject with data glove imitated the same motion with a dexterous robot hand which was moving according to a certain mathematical function. Autoregressive models were adapted to the matching, where each joint angle in the robot and data glove data of the human were used as object and explanatory variables respectively. The partial regression coefficients were estimated by means of singular value decomposition with a system-noise reduction algorithm utilizing statistical properties. The experimental results showed that the robot hand was controlled with high accuracy with small delay, suggesting that the method proposed in this study is proper and easy way and is adaptive to many other systems between a pair of motion-measurement device and output device.

The authors propose a system for searching the shape of human hands and fingers in real time and with high accuracy, without using any special peripheral equipment such as range sensor, PC cluster, etc., by a method of retrieving similar image quickly with high accuracy from a large volume of image database containing the complicated shapes and self-occlusions. In designing the system, we constructed a database in a way to be adaptable even to differences among individuals, and searched CG images of hand similar to unknown hand image, through extraction of characteristics using high-order local autocorrelational patterns, reduction of the amount of characteristics centering on principal component analysis, and prior rearrangement of data corresponding to the amount of characteristics. As a result of experiments, our system performed high-accuracy estimation of human hand shape where mean error was 7 degrees in finger joint angles, with the processing speed of 30 fps or over.

Pneumatic pressure, which is easy enough to be handled in comparison with hydraulic pressure and is endowed with high safety, is available for a power source of a robot arm to be utilized in concert with human beings to do various types of work. But pneumatic pressure is so low in comparison with hydraulic pressure that an air cylinder having a diameter long enough and stroke wide enough is required to obtain great output power. In this study, therefore, the investigation was made with layout of air cylinders and transmission mechanisms of the motion power directed toward the driving joints to be followed by development of a new humanoid robot arm with seven degrees of freedom in which air cylinders are compactly incorporated. To be concrete with this, contrivance was made with an endoskeleton structure allowing almost all of the structure materials of the individual arm joints to be shared by the air cylinder with incorporation of the air cylinder in the axes of the upper arm joint and forearm joints by paying attention to the fact that the cylinder itself has high strength. The evaluation experiments driving the robot arm referred to above were conducted by means of I-PD control. The results suggested that the mechanism of the robot with seven degrees of freedom having pneumatic actuators proposed in this study is useful as the humanoid robot arm. The quick and accurate motions were accomplished with I-PD control which is relatively easy to be dealt with but not suitable for non-linear actuator system.

In this study, a CG animation tool was designed that allows interpolation and extrapolation of two types of repeated motions including finger actions, for quantitative analyses of the relationship between features of human motions and subjective impressions. Three-dimensional human motions are measured with a magnetic motion capture and a pair of data gloves, and then relatively accurate time-series joint data are generated utilizing statistical characteristics. Based on the data thus obtained, time-series angular data of each joint for two dancing motions is transformed into frequency domain by Fourier transform, and spectral shape of each dancing action is interpolated. The interpolation and extrapolation of two motions can be synthesized with simple manner by changing an weight parameter while keeping good harmony of actions. Using this CG animation tool as a motion synthesizer, repeated human motions such as a dancing action that gives particular impressions on the observers can be quantitatively measured and analyzed by the synthesis of actions.

The purpose of this study is to design a humanoid robotic hand system that is capable of conveying feelings and sensitivities by finger movement for the non-verbal communication between men and robots in the near future. In this paper, studies have been made in four steps. First, a small-sized and light-weight robotic hand was developed to be used as the humanoid according to the concept of extracting required minimum motor functions and implementing them to the robot. Second, basic characteristics of the movement were checked by experiments, simple feedforward control mechanism was designed based on velocity control, and a system capable of tracking joint time-series change command with arbitrary pattern input was realized. Third, tracking performances with regard to sinusoidal input with different frequencies were studied for evaluation of the system thus realized, and space- and time-related accuracy were investigated. Fourth, the sign language motions were generated as examples of information transmission by finger movement. A series of results thus obtained indicated that this robotic hand is capable of transmitting information promptly with comparatively high accuracy through the movement.