Search

The kinesthetic illusion (KI) is a phenomenon in which transcutaneous vibration stimulation applied to a tendon induces the illusion of body movement. This phenomenon has potential applications in rehabilitation and virtual reality (VR). To effectively apply KI, precise vibration stimulation parameters (such as sine wave vibration with controlled frequency, acceleration, and pressing force against the tendon) must be delivered to various body parts. Thus, to realize this phenomenon, miniature vibrators must be developed and controlled. In this study, we developed a compact vibrator using a miniature voice coil motor to induce KI. We constructed a control system to regulate the target acceleration even in the presence of variations in the reactive forces from the tendon. Using the developed vibrator, we applied KI to the biceps brachii tendon and determined the optimal vibration stimulation conditions. The results revealed that the optimal vibration stimulation conditions for each subject’s biceps brachii muscle were related to the thickness of the upper arm. This result demonstrates the ability to determine guidelines for optimal stimulation conditions based on the physical characteristics of each individual participant. The increased ease of experiencing KI is expected to pave the way for rehabilitation using vibrators in wearable robots.

To develop a tactile display, we focused on the Velvet Hand Illusion (VHI), which is a tactile illusion phenomenon. The most important feature of VHI is that VHI is not generated in one wire but is generated in two or more wires. This means that we recognize the area surrounded by wires as a Gestalt and a smooth surface sensation is generated in the Gestalt. We assume that the VHI mechanism is related to the law of closure and the law of common fate in Gestalt theory. In this paper, we investigate the relationship between VHI and the law of closure by means of variation in a phase difference of two wires’ cyclic movement, and formulate VHI variation, taking into account the law of closure. We try to divide the law of closure into two factors: one of them is a factor of translation and the other is a factor of elasticity. We formulate the tactile Gestalt and verify the validity of this formulation by comparing the result of the psychophysical experiment to the estimation via the formulation. This work shows that the law of closure in the tactile Gestalt consists of the translation factor and the elasticity factor, and the VHI mechanism is described by the formulation of the tactile Gestalt.

In haptic virtual reality (VR), there are two important challenges: one is the difficulty of reproducing a surface feeling with haptic devices, and the other is the presentation method used for the display. We developed a tactile mouse using palm presentation for the former challenge to tackle the issue, “which tactile perception is superior for texture recognition, active or passive touch?” In a psychophysical experiment, two oblique edges of dot-patterns are presented consecutively as simple textures, and human subjects compare them to determine which is larger. We evaluated the precision of perception using the difference threshold of the edge angles calculated by the constant stimuli method. Experimental results show that the perception precision at low edge movement speeds (45 and 90 mm/s) was higher than that at high speeds (130 and 170 mm/s), and moreover, that there was no significant difference in precision of the edge angle perception between active and passive touches. The former finding seems to be caused by how well the mechanoreceptive unit handles uneven surfaces. The latter finding is due to the mechanism of the efference copy of a motor signal provided from the motor cortex not having a significant influence on texture recognition. The tactile image deterioration induced by the object movement might be compensated for with information processing in the central nervous system, which keeps stable tactile image without help from the efference copy. This work contributes to developing the haptic device which provides visually impaired persons with the tactile map.

Time-evolving tactile sensations are important in communication between animals as well as humans. In recent years, this research area has been defined as “tactileology,” and various studies have been conducted. This study utilized the tactile Gestalt theory to investigate these sensations. Since humans recognize shapes with their visual sense and melodies with their auditory sense based on the Prägnanz principle in the Gestalt theory, this study assumed that a time-evolving texture sensation is induced by a tactile Gestalt. Therefore, the operation of such a tactile Gestalt was investigated. Two psychophysical experiments were conducted to clarify the operation of a tactile Gestalt using a tactile illusion phenomenon called the velvet hand illusion (VHI). It was confirmed that the VHI is induced in a tactile Gestalt when the laws of closure and common fate are satisfied. Furthermore, it was clarified that the tactile Gestalt could be formulated using the proposed factors, which included the laws of elasticity and translation, and it had the same properties as a visual Gestalt. For example, the strongest Gestalt factor had the highest priority among multiple competing factors.

A tactile record and playback system will progress tactileology—a new cross-disciplinary field related to tactile sensations—as it will enhance its use in the instruction, archiving, and analysis of human manipulation. In this paper, we describe two key devices for achieving tactileology: a tactile sensor capturing human tactile sense (fingernail color sensor) and a robotic tactile sensor, both of which can detect not only normal force but also tangential force. This is beneficial because people manipulate objects and tools in various ways, such as grasping, picking, and rubbing. The fingernail color sensor registers the three-dimensional (3D) force applied to a fingertip by detecting the fingernail color change caused by blood distribution under the fingernail, which can be observed with green illumination and a miniature camera. Since detecting this color change is more complicated than using a robotic sensor, the relationships between the image and 3D force are learned using a convolutional neural network (CNN). In the robotic sensor, the 3D force applied to a robotic finger transforms into a bright area using an illuminated acrylic core, a rubber robotic finger skin, and a miniature camera. We measure normal force and tangential force by the brightness and movement of the bright area, respectively. Using a force gauge or an electronic scale for measurement, we perform a series of evaluation experiments. The experimental results show that the precision of both the fingernail color sensor and the robotic tactile sensor are sufficient for our system.

Hardness representation in VR is one of the important problems to create virtual touch feeling as if the feeling is caused by real touch. In this study, we are attempting to improve the hardness representation method by combining the pseudo-haptics and tactile stimuli, which was presented in our previous research. In the current study, we investigated the ability of both of these methods to express tactile hardness stimulation: in Experiment A hardness was generated solely by visual stimulation using CG; and in Experiment B hardness was generated solely by the dot-matrix display. Based on the results of Experiments A and B, in Experiment C we conducted psychophysical experiments on the ability to express tactile hardness by combining the effects of pseudo-haptics and the tactile stimuli. In Experiment C, we were able to express six levels of distinguishable hardness, while only four and two levels were observed in Experiments A and B, respectively. In addition, the relationship between hardness evaluation and the six levels shows high linearity with R2 = 0.98.

To enhance virtual reality (VR) generated by tactile displays, we have focused on a novel tactile illusion, called the Velvet Hand Illusion (VHI). In VHI, moving two parallel wires back and forth between the two hands leads humans to perceive a velvet-like surface between their hands. In earlier studies, we revealed that the intensity of VHI could be controlled by a ratio ( r / D ), where r and D are the wire stroke and wire distance, respectively. According to these findings, we investigate in this study whether a common tactile display is able to produce VHI, and whether the ratio can also control VHI intensity. We prepare a dot-matrix display as a tactile display in which moving one line of the display’s pins is considered as a wire pattern. We investigate the VHI intensity with regard to changing the stroke r and the line distance D using paired comparison. Experimental results show that the VHI intensity is increased or decreased by changing r and D . We conclude that VHI can be created by the tactile display, and the intensity of VHI is controlled by changing the ratio of r / D .

This paper presents the development of new Humanoid Robot Control Architecture (HRCA) platform based on Common Object Request Broker Architecture (CORBA) in a developmental biped humanoid robot for real‐time teleoperation tasks. The objective is to make the control platform open for collaborative teleoperation research in humanoid robotics via the internet. Meanwhile, to generate optimal trajectory generation in bipedal walk, we proposed a real time generation of optimal gait by using Genetic Algorithms (GA) to minimize the energy for humanoid robot gait. In addition, we proposed simplification of kinematical solutions to generate controlled trajectories of humanoid robot legs in teleoperation tasks. The proposed control systems and strategies was evaluated in teleoperation experiments between Australia and Japan using humanoid robot Bonten‐Maru. Additionally, we have developed a user‐ friendly Virtual Reality (VR) user interface that is composed of ultrasonic 3D mouse system and a Head Mounted Display (HMD) for working coexistence of human and humanoid robot in teleoperation tasks. The teleoperation experiments show good performance of the proposed system and control, and also verified the good performance for working coexistence of human and humanoid robot.

We are developing an optical three-axis tactile sensor capable of acquiring normal and shearing force to mount on a robotic finger. The tactile sensor is based on the principle of an optical waveguide-type tactile sensor, which is composed of an acrylic hemispherical dome, a light source, an array of rubber sensing elements, and a CCD camera. The sensing element of the silicone rubber comprises one columnar feeler and eight conical feelers. The contact areas of the conical feelers, which maintain contact with the acrylic dome, detect the three-axis force applied to the tip of the sensing element. Normal and shearing forces are then calculated from integration and centroid displacement of the grayscale value derived from the conical feeler's contacts. To evaluate the present tactile sensor, we conducted a series of experiments using an x-z stage, a rotational stage, and a force gauge. Although we discovered that the relationship between the integrated grayscale value and normal force depends on the sensor's latitude on the hemispherical surface, it is easy to modify the sensitivity based on the latitude to make the centroid displacement of the grayscale value proportional to the shearing force. When we examined the repeatability of the present tactile sensor with 1,000 load/unload cycles, the error was 2%.

The CT (Computed tomography) method is very effective for making thinner optical waveguide-type tactile sensors. In a previous paper, the authors established the architecture of a CT tactile sensor and evaluated its principle using a series of computer simulations. As a result, the LU decomposition method showed better noise robustness compared to the ART method. On the basis of the simulations, we develop an experimental CT tactile sensor comprised of infrared diodes, phototransistors, an acrylic plate and a black rubber sheet. In the present study, the LU decomposition method is employed and we determine the validity of the algorithm by examining use of a loading machine produced for the CT tactile sensor. In a series of experiments, it is found that absorption of light intensity increases monotonically with increase of applied force and that the present reconstruction method can be applied to not only simply but also multiply connected contact domains. The estimated position of the pressure centroid possesses a rather large error of 4.9 mm, which is 10.8% of a segment of the sensing area.

The authors developed advanced haptic displays capable of stimulating the muscles and tendons of the forearms and tactile receptors in fingers to investigate tactile and force effects on simultaneous presentation. Display A is comprised of a master hand with two sets of tactile display with a 4-by-6 array of stimulus pins driven by micro-actuators and an articulated manipulator. Display B is comprised of an articulated manipulator and an 8-by-8 array type tactile display developed in a previous paper. A series of experiments was performed using the above A and B displays to verify the presentation capability of this display type. In Experiment I, subjects grasped virtual pegs and judged their diameters. In Experiment II, subjects tried to insert the pegs into holes. In Experiment III, the crossed-angle of a comparison texture was adjusted to bring it as close as possible to the standard texture fixed during experiments. Since diameter discrimination and insertion precision of the virtual peg were increased by tactile information, tactile-force presentation was effective for peg-in-hole for relatively large clearance. On the other hand, recognition capability for virtual texture was not enhanced compared to a mouse-mounted tactile display previously developed. While the pressure display is effective for instant of touch and peg rotation representations, rotation tactile imaging is not always effective for texture recognitions.

In order to create a robotic tactile sensor of thin shape, a new optical tactile sensor is developed by applying a CT (Computer Tomography) algorithm. The present tactile sensor is comprised of infrared emitting diode arrays, receiving phototransistor arrays and a transparent acrylic plate and a black rubber sheet with projections. Infrared rays emitted from the diode array are directed into one end of the plate and their intensity distribution is measured by the phototransistor array mounted on the other end. If the CT algorithm is directly applied to the tactile sensor, there are two shortcomings: the shape of the sensing area is limited to a circular region and there is a long calculation time. Thus, a new CT algorithm oriented to tactile sensing is proposed for overcoming these problems. In the present algorithm, a square sensing area is divided into an N-by-N array and algebraic equations are derived from the relationship between the input and output light intensities on the assumed light projections. Several reconstruction methods are considered for obtaining pressure values caused in the squares. In the present study, the ART (Algebraic Reconstruction Technique) and LU decomposition methods were employed, and these methods were compared to select the best reconstruction method. In a series of simulations, it was found that the LU decomposition method held an advantage for the present type of tactile sensor because of its robustness against disturbance and short calculation time.

Since our ultimate target is to realize a simple and inexpensive rehabilitation system of kinesthetic illusion and apply it to rehabilitation training, we need to miniaturize the vibration stimulus device and systematize the vibration stimulus conditions to freely induce and control the illusion. In this paper, we developed a desktop kinesthetic illusion inducement and evaluation system that allows us to investigate the sensory properties of the illusion. When the contact force of a contact head is under 1.5 N, our system can apply vibration stimuli of 100 m/s2 to the tendon between 50 and 300 Hz. Experiments with this system induced kinesthetic illusion of an extension at the right hand joint in all five subjects. We confirmed the efficacy of an estimation system of sensory properties and enhanced gatherings of the vibration stimulus conditions to induce and control the illusion.

Tactile sensors and their data processing are very important in enabling robots to handle objects. With information processing by biological organisms, stochastic resonance (SR) can enhance sensitivity by superimposing proper noise upon undetectable weak signals to detect the target signal. To investigate the SR of human tactile sensation and elucidate the mechanism of tactile SR for the development of a new tactile sensor, we performed a series of psychophysical experiments using tangential vibration with 2.5-mm and 8-mm-sized stimulus points. We examined the difference threshold (difference limen; DL) variation obtained from these experiments to clarify which conditions of vibration direction and stimulus size cause the strongest SR. The experimental results show that neither normal nor tangential DL is significantly affected by stimulus point size. Moreover, tactile sensing precision is enhanced by appropriate noise. The characteristics of SR, with normal vibration obtained from our prior study is quite different from that with tangential vibration.

This paper describes the development of an autonomous obstacle-avoidance method that operates in conjunction with groping locomotion on the humanoid robot Bonten-Maru II. Present studies on groping locomotion consist of basic research in which humanoid robot recognizes its surroundings by touching and groping with its arm on the flat surface of a wall. The robot responds to the surroundings by performing corrections to its orientation and locomotion direction. During groping locomotion, however, the existence of obstacles within the correction area creates the possibility of collisions. The objective of this paper is to develop an autonomous method to avoid obstacles in the correction area by applying suitable algorithms to the humanoid robot's control system. In order to recognize its surroundings, six-axis force sensors were attached to both robotic arms as end effectors for force control. The proposed algorithm refers to the rotation angle of the humanoid robot's leg joints due to trajectory generation. The algorithm relates to the groping locomotion via the measured groping angle and motions of arms. Using Bonten-Maru II, groping experiments were conducted on a wall's surface to obtain wall orientation data. By employing these data, the humanoid robot performed the proposed method autonomously to avoid an obstacle present in the correction area. Results indicate that the humanoid robot can recognize the existence of an obstacle and avoid it by generating suitable trajectories in its legs.

This report presents a basic contact interaction-based navigation strategy for a biped humanoid robot to support current visual-based navigation. The robot's arms were equipped with force sensors to detect physical contact with objects. We proposed a motion algorithm consisting of searching tasks, self-localization tasks, correction of locomotion direction tasks and obstacle avoidance tasks. Priority was given to right-side direction to navigate the robot locomotion. Analysis of trajectory generation, biped gait pattern, and biped walking characteristics was performed to define an efficient navigation strategy in a biped walking humanoid robot. The proposed algorithm is evaluated in an experiment with a 21-dofs humanoid robot operating in a room with walls and obstacles. The experimental results reveal good robot performance when recognizing objects by touching, grasping, and continuously generating suitable trajectories to correct direction and avoid collisions.

This paper describes the development of an autonomous obstacle-avoidance method that operates in conjunction with groping locomotion on the humanoid robot Bonten-Maru II. Present studies on groping locomotion consist of basic research in which humanoid robot recognizes its surroundings by touching and groping with its arm on the flat surface of a wall. The robot responds to the surroundings by performing corrections to its orientation and locomotion direction. During groping locomotion, however, the existence of obstacles within the correction area creates the possibility of collisions. The objective of this paper is to develop an autonomous method to avoid obstacles in the correction area by applying suitable algorithms to the humanoid robot's control system. In order to recognize its surroundings, six-axis force sensors were attached to both robotic arms as end effectors for force control. The proposed algorithm refers to the rotation angle of the humanoid robot's leg joints due to trajectory generation. The algorithm relates to the groping locomotion via the measured groping angle and motions of arms. Using Bonten-Maru II, groping experiments were conducted on a wall's surface to obtain wall orientation data. By employing these data, the humanoid robot performed the proposed method autonomously to avoid an obstacle present in the correction area. Results indicate that the humanoid robot can recognize the existence of an obstacle and avoid it by generating suitable trajectories in its legs.