Although eyes and upper limbs work together over the whole course of arm movement, vision usually dominates in visual-haptic perception. The dependence of the brain on visual information is demonstrated by the wide variety of visual illusions, such as “shade and shape,” that have been developed. In order to quantitatively measure upper-limb motion, a haptic device can be used to obtain numerical data. Although, as the name suggests, such a device is capable of transmitting force, human perception mechanisms tend not to measure force accurately owing to interference. In this paper, we analyze the role played by visual information in line drawing. In experiments where participants were asked to estimate the length of a line using a haptic device operated by an experimenter and then to draw a line on their own, there was a tendency to draw a longer line when their eyes were open. These results reinforce the importance of visual information to length recognition in drawing.

Motion control algorithms were proposed for a 9-DOF finger-arm robot by using the finger manipulability obtained in a previous study. However, in the previous study, only methods for achieving unconstrained movement of the finger-arm robot were discussed. In this paper, the authors propose a novel method for having a finger-arm robot complete a constrained task by integrating impedance control with manipulability control of the finger. First, methods of applying the previous heuristic method to the passive impedance control and the active impedance control were developed; and experiments were performed to demonstrate the features. Then, an impedance control combined with the steepest ascent method to modulate the manipulability of the finger was proposed. The proposed method demonstrates a strong performance even when a dynamic external force is applied to the finger. By using the proposed method, the arm actively moves along a direction to effectively maintain the moving potential of the finger during both the unconstrained and the constrained tasks.

This paper describes the effect of Muller-Lyer illusion on a reaching movement just after the visual and haptic/kinesthetic cues are simultaneously presented. First, a standard experiment on this visual illusion is conducted by means of the most typical way so as to make sure that participants can experience this illusion; the result shows that all the subjects are deceived by the illusion figure as in many previous results. As the next step, the subjects are asked to physically trace one of three lines-normal line and lines with feathers of an arrow-with the same length displayed on an LCD. After a few traces, the line suddenly vanishes, and then the subjects retrace the invisible line based on only their memory and somatic sensations. During this task, we measure the trajectory of fingertip from a start to the goal using a motion capture system. The result indicates that the Muller-Lyer illusion dominantly affects the reaching task although the haptic/kinesthetic cue was also given just before the task. Thus, this result implies that the visual illusion affects the motion planning, which partly supports a planning-motion model.

This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environment is available. Generally, it is widely said that this type of learning method is not appropriated to obtain dynamic motions because Markov property is not necessarily guaranteed during the dynamic task. However, in this study, we try to avoid this problem by embedding the dynamic information in the robotic state space; the applicability of the proposed method is considered using both the real robot and dynamic simulator. This paper, in particular, discusses how the robot with 5-DOF, in which the Q-Learning algorithm is implemented, acquires a giant-swing motion. Further, we describe the reward effects on the Q-Learning. Finally, this paper demonstrates that the application of the Q-Learning enable the robot to perform a very attractive giant-swing motion.

This paper discusses human weight perception using a haptic device. The objective of this study is to reveal the characteristics in human force sensations, which are difficult to examine in a real environment. Further, we aim to apply the perceptual mechanisms to multimedia applications as the final target. In this study, we particularly examine the weight discriminative powers for various weight changes. Expanding our previous study, we compare the difference thresholds for the weight addition and removal during a goal-directed lifting. A statistical analysis implies that our weight discriminative power for the weight addition tends to improve in the deceleration process. As for the weight removal, the weight discriminative power declines in the deceleration process due to the inertia effect in the vicinity of the target height. In addition, this study tries to reveal the weight perception when the load force is gradually changed. The result implies that the time variation in the load force holds the tremendous potential to enable us to experience attractive force sensations and haptic illusions.

Human beings usually locate their hand at the position with a higher moving potential in order to easily deal with various situations. Inspired by the human hand-arm movement, this study proposes a motion control issue for a serial-linkage finger-arm robot according to Wf.

The main purpose of this study is to apply the mechanism of human weight perception to multimedia applications. When a start and the goal points are given in the human motion, the velocity profile has a unimodal profile including the acceleration and deceleration zones. In such case, it is widely said that the motion control becomes more accurate in the deceleration zone for the final approach. Hence, it is assumed that the sensing ability also improves. This study challenges to confirm the hypothesis with weight stimuli generated by a force display device. As a preliminary experiment, this study confirms that our device enables the evaluation of human perception by tracing Weber's experiment in virtual reality; the obtained difference threshold (DL: Differenz Limen) almost agrees with the previous results. The difference threshold is a very important factor, which means perceptual threshold for weight changes. We further attempt to clarify the mechanism of the human weight perception for sudden weight changes during the lifting process. Based on individual lifting profiles, this study suddenly changes the load force in the two zones, and examines the difference thresholds of each subject. The results demonstrate that the human weight perception tends to become more sensitive in the deceleration zone during the lifting process. These results also imply the effectiveness of force display devices for physical experiments.

This paper describes a technical education program for high school students that comprises an image information processing system, stereo vision technology and control experiments involving a simple and compact robot equipped with a stereo vision system. Education results show that this program can yield excellent results to obtain both hardware and software technology and also to obtain data on the control experiences of actual robots. In addition, this program could provide high school students an interesting experience on both constructing a robot and programming it; this can be verified by questionnaires that the students fill out at the end of the program. Finally, the results also indicate that this program is an effective education system for high school students to gain exposure to system technology including software and hardware technology.

The advancement of multimedia services including audio/visual media has been rapid. The applications of cellular phones, in particular, have increased by using these technologies. In addition, if force telecommunication were realized, force information would become a next leading factor in the multimedia service. In this field, a robotic master/slave system is a leading candidate. This system has been studied as a teleoperation system between an operator and an environment; the operator controls only the master device whereas the slave device is never controlled. For multimedia applications, such systems require flexibility and bidirectionality because force telecommunication must consider the interactions between users. This paper details the fundamental issues of force communication from a viewpoint of human perception. With regard to the control system, this study uses an integrated hybrid control master/slave system that helps to find a key factor of equal bilateral force telecommunication in the sensory aspect. The employed system has a function to change the proportion of force display to position display by varying a weight parameter. We discuss the basic control performance of a force telecommunication system and evaluate qualitative feelings of users by using a psychological evaluation method

This paper investigates the motion forms of robots generated by the Q-Learning algorithm during the learning process. We analyzed the manner in which a caterpillar robot, which performs looping motions using two actuators, acquires advance actions by focusing on the process. By observing a series of processes, we confirmed that various motion forms appeared or disappeared as a result of their interactions with the learning process and approach an optimum motion form. In most algorithms, such motion forms cannot appear in the learning process because its framework is almost predetermined by the teacher data, and the cost functions for learning cannot be usually considered as a continuous process. The characteristics of reinforcement learning are very interesting from the viewpoint of biological evolution. This paper describes the effects of the interaction between the robot kinematics and the environment as a direct result of changing the environment. In addition, this study challenged the acquisition of two-dimensional motions with a starfish robot having four actuators. The result demonstrates that the robot can obtain a reasonable motion from the complicated relationships with the environment by skillfully employing its structure. Moreover, this paper implies that the reward manipulation may give a new insight for the learning process by the investigations performed in this study. This paper examines the possibility of the reward combinations for generating arbitrary motions.

Human beings cannot control a position of sphere on the disk without seeing it. Because under such a condition, as we determine the position and estimate the motion of sphere by use of visual information, it is very difficult for human beings to control it using only tactile or force information of a hand. This is why the tactile and the force information are less quantitative for human beings than the visual information. On the other hand, a robot can deal with this qualitative information as quantitative values. Therefore, the robot seems to have the possibility that it carries out such difficult tasks for human beings using only force information. In this paper, we propose the estimation method of the position of sphere (made of crystal) on the disk from the force information measured with three-directional force sensors. Then, we tried to examine whether the robot fingers can control the motion of sphere on the disk using only these force information. Actually, the position and the velocity information estimated from force information enable the robot fingers to control the sphere by applying a simple PD control algorithm. Moreover, this paper adds Lyanpunov’s stability analysis of the proposed control algorithm. Finally, this results show new robot task which human beings cannot realize, whose demonstration is very interesting.

In this paper, by focusing on weight perception, we attempted to clarify a perceptual mechanism using functions of the haptic interface. We especially examined the weight perceptual mechanism when the weight of an object suddenly changed, which does not take place in our natural life. This experimental condition can only be realized by using the advantage of the haptic interface. The results show the difference in the perceptual threshold due to addition and reduction of the weight. Moreover, the results indicate that subjects can also correct the supporting force corresponding to the sudden change in the weight when they could not sense the change. Namely, it implies that subjects adjust the supporting force under an imperceptible state, which may indicate an interesting muscular motion under a state of unconsciousness.

Recently, the haptic interface system (one of a variety of force display devices) has attracted great interest as a new virtual reality technology, stimulating vigorous research. Most reports deal with methods of constructing a haptic interface system or the development of new devices having with a particular mechanism, and the various methods suitable for force display. However, it is also necessary to clarify the relationship between the virtual dynamics characteristics of a system and a human being's feelings in order to present the accurate force sensation from virtual environment. In this paper, we evaluate the force sensations experienced by human beings with the psychological experiments that examine perceptual illusion phenomena, including the horizontal-vertical illusion and the size-weight illusion. These results show that perceptual illusions occurring in a real environment can be also reappeared in a virtual environment. Therefore, perceptual illusions may have the potential for application to virtual reality. Moreover, the characteristics of perceptual illusions can be examined by changing the virtual dynamics parameters of the haptic interface. Finally, this paper shows that the haptic interface is a very effective tool for the investigation of perceptual illusions.

Presents a new method utilizing a genetic algorithms to search for initial values for a nonlinear optimization process in multi-viewpoint stereo measurement. First, the authors take a one dimensional matrix called "individual" which consists of parameters to be determined. Next, the authors form a population which consists of several individuals. The authors perform three kinds of genetic operation on the population, that is, crossover, mutation and selection, which evolve the population to fit the environment. The authors reiterate this evolution process and use the evolved result as the initial values for the iteration calculation. The efficiency, of this method is confirmed by simulation and an outdoor experiment.>

An estimation method is presented for accurately determining the relationship between viewpoints and object positions simultaneously by integrating stereo data from multi-viewpoints whose relationship is unknown. With this method both the relationship and the object positions are estimated by minimizing the sum of square errors in the image coordinates. The calculation is performed with the nonlinear optimization method because the multi-viewpoint stereo measurement system is a nonlinear system. Therefore, this method can be applied to an arbitrary multi-viewpoint stereo measurement system, whereas almost all conventional methods can only be applied to linear cases. A simulation is used to investigate the influence of the relative viewpoint position parameters on the accuracy with which object positions are determined in a three viewpoint stereo measurement. The effectiveness of this method is confirmed experimentally by actual outdoor measurements.

Feedforward feedback neural network controllers have been proposed. These controllers use the sum of neural network output and conventional controller output as the object plant input. The authors proposed an adaptive type feedforward feedback controller using a neural network and confirmed its characteristics. However, th learning type neural network controller is also attractive for servo control applications. Therefore, this paper proposes a learning type feedforward feedback neural network controller for discrete time dynamic systems. Simulated results using a second order plant confirm the characteristics of the proposed controller.

A practical neural network design method for the identification of both the direct transfer function and inverse transfer function of an object plant is proposed. As a practical application of the direct transfer function identifier, a nonlinear plant simulator is also proposed. Simulated and experimental results for a second-order plant show that identification can be satisfactorily achieved and that neural network identifiers can represent nonlinear plant characteristics very well. The characteristics of a neural network direct controller with a feedback control loop, which uses the learning results of the inverse transfer function identifier, is also proposed and confirmed.>

The authors propose an object shape detection system using a force/torque sensor and a flexible/inflexible insensitive probe. A tactile sensing method which makes it possible to estimate a contact position on the probe only by measuring contact force has been developed. Though the probe does not have any sensitive devices. the method derives the contact position from force information measured by the force/torque sensor. When the probe bends according to the applied force, the method compensates for the probe deflection by estimating its transformation based on force/torque sensor information. It has been applied to a manipulator system, and object shape detection experiments have been conducted using a cylindrical probe. Shapes of 3D objects have successfully been reproduced.>

We propose a new approach for mcasuring 30 positions of target objects using stereo vision system. In stereo vision metrology for natural scenes , automatic recognition of targets and detcrminination of corresponding points arc strongly desired , which technique as of today is so poor that these processes are relied on human asislance. Automatic recognition and stereo correspondensc of telephone poles in a pair of natural scenes is realized by using an algorithm considering specifications of the targets, such as diameter, height, installation condition, through four steps, that is, [ I] Search region resDiction, [ O] Recognition, [U] Correspondence and [IV] Examination.

An autotuning method for the optimum sigmoid function of neural networks is proposed. It is based on the steepest descent method. Simulated results using a learning-type direct controller confirm both the practicality and the characteristics of the autotuning method.

The basic stability characteristics of the nonlinear hybrid control system are clarified by using Lyapunov's method in relation to autonomous systems. The fundamental stability condition of hybrid control is evaluated by using a hybrid control scheme, the friction effect, an additional phase lag (dead time), and the digital control effect. The sampling delay (dead time) causes a large additional phase lag, which in turn causes instability. Moreover, the stability results confirm that the hybrid control scheme and digital control effect adversely affect hybrid control stability even if the fundamental stability condition is satisfied.>

The authors attempt to clarify neural network (NN) controller characteristics by comparison with the adaptive control theory. The authors clarify the classification of the NN controller architecture and the dynamic NN structure. Comparison between the NN controller and the adaptive controller clarifies that the framework of a linear two-layer NN-type controller is the same as that of adaptive control and the nonlinear three-layer NN (PDP type) is a nonlinear extension of the adaptive control. The stability characteristics of the NN control system are discussed. NN controller experiments are demonstrated using a force control servomechanism. Experimental results suggest that the nonlinear sigmoid function of the NN can compensate for the nonlinear plant effect.>

The basic features of the learning-type neural network (NN) controller are clarified. Analytical and experimental results show its stability, convergence and generalization ability compared with the adaptive-type NN and conventional learning control. As an application of the learning-type NN, a nonlinear optimum regulator is presented whose learning ability can obtain optimum conditions without solving a difficult Riccati equation. Moreover, it can be applied to a nonlinear control system because of its nonlinear mapping ability, although the conventional optimum regulator can only be applied to a linear system. Finally task planning is proposed in terms of skill acquisition using the learning-type NN, which implies the possibility of making an interface with an upper symbolic-level control.>

Describes the auto-tuning of feedback gains for a small tunnelling robot. The authors (1989) have already proposed the directional control method that the head angle of the control input is the sum of the deviation multiplied by feedback gain Kp and the angular deviation multiplied by feedback gain Ka. In this paper, they use a neural network to obtain feedback gains Kp and Ka. The inputs of the neural network are an initial deviation and an initial angular deviation. The outputs of the neural network are the feedback gains Kp and Ka. This neural network learns from the deviation errors. The optimum gains obtained by the proposed method agreed with the optimum gain obtained by trial and error. The neural network which can apply to any initial deviations were formed by using plural initial deviations in learning. Moreover, this method can tune the optimum gains to any design line. The results showed the validity of the proposed auto-tuning method.>

Proposes a digital control method for master-slave manipulator systems which can realize high-fidelity telemanipulation. In the discrete-time system, the time-delay of sensor signals and the zero order hold effect of command signals on actuators should be considered to make the systems stable. The authors first analyze the dynamic control method of a master-slave system in discrete-time for the stability problem, which can realize high-fidelity telemanipulation in continuous-time. Secondly, using the results of the stability analysis, the robust control scheme for the master-slave system is proposed, and the validity of this scheme is finally confirmed by simulation.>

NN (neural network) controller characteristics are clarified by comparison with the adaptive control theory. The authors explain the classification of the NN controller architecture and the dynamic NN structure. A comparison between the NN controller and the adaptive controller shows that the framework of a linear two-layer NN controller is the same as that of the adaptive controller, and that the nonlinear three-layer NN (PDP, or parallel distributed processing type) is a nonlinear extension of the adaptive control. The stability characteristics of the NN control system, which shows the robustness effect of the generalized delta rule, the plant and the NN mapping function, are treated. Finally, NN controller experiments are demonstrated using a force control servomechanism. Experimental results suggest that the nonlinear sigmoid function of the NN can compensate for the nonlinear plant effect.>

An object shape detection system using a force/torque sensor and an insensitive probe is proposed. the development of a tactile sensing method is which makes it possible to estimate a contact position on the probe by measuring only contact force is presented. Though the probe itself is not sensitive, the method derives the contact position from force information measured by the sensor. The estimated values do not depend on either the magnitude or the direction of the force. The method can be with any probes of any shape and material. This method is applied to a manipulator system, and object shape detection experiments are conducted using two types of probes. Shapes of three-dimensional objects are successfully reproduced. The results confirm that the method enables the manipulator system to detect objects without precise control.>

The difference between master/slave and hybrid two-arm position/force control is clarified. Experimental results have shown that the hybrid control law yields smaller force errors, better tracking of sine input, and faster rise time for a step input than the master/slave control law. The master/slave control for both step and sine input resulted in a maximum force error of 75%, wherein the hybrid scheme had only 34% maximum error for the step command and 18% maximum error for the sine command. The reason for difference is that in master/slave control there is no sharing of information (errors) between the arms, and the slave must react to the master. In hybrid control the arms share the internal force error and position error, i.e. they cooperate when they move.>

Conditions are presented for the global asymptotic stability of the hybrid position/force control of robot manipulators, using Lyapunov's direct method. Although hybrid control schemes have been studied in depth, the stability problem has not been clarified completely. The authors deal with the stability of the hybrid control scheme in Cartesian coordinates of the work space, especially from the viewpoint of coupling between position and force control. Results show not only the global asymptotic stability conditions but also the physical interpretation or meaning of the stability conditions by citing an example of a two-degree-of-freedom manipulator.>

It is shown that a servomechanism with only position/velocity functions can obtain a force control function using the adaptive theory (model-referenced adaptive system and model-referenced control). Experimental results of both the servomechanism and the single-degree-of-freedom force control of the manipulator show that this method leads to suitable force control when the object stiffness changes greatly. The advantage of this method is that a force control function is achieved by implementing software to identify the object stiffness without changing hardware.>