Akihide Shibata

Tongue elasticity sensing with muscle contraction monitoring

This paper discusses a elasticity sensing system that is able to evaluate tongue elasticity in vivo. We utilize an equivalent Youngs modulus of tongue, which is defined by the applied pressure divided by the tissue strain. We also introduce an index of muscle contraction by using an electromyographic (EMG) signal for judging whether the increase in elasticity is caused by a muscle contraction or a disease. By using a experimental system composed of a gripper-type elasticity sensing system and an EMG sensor, we confirm the validity of the proposed method. Through experiments, we show that the equivalent Youngs modulus of tongue under the muscle contraction is four times larger than that under no muscle contraction.

Experimental study of creep response of viscoelastic contact interface under force control

Viscoelastic materials are known to exhibit temporal response that changes force or displacement at the contact interface under position or force control, respectively. In this paper, we conduct experimental study using force control to explore and observe creep phenomenon in robotic grasping in order to better understand the nature of such contact interface, which has been widely used in soft robotic fingers, robotic feet, and contact surface of robotic arms. We found that the creep response under a constant external force exhibits the characteristics of exponentially increasing or decreasing temporal response. Such characteristics are similar in nature to those found in the relaxation response of viscoelastic materials when the grasping is under position control. Two different types of creep responses are found, depending on the state of grasping. Both Types I and II in creep response mirror the Types I and II in relaxation response. We also found that different loading rates under force control result in different elastic response, in addition to the temporal response. This is an interesting finding because the Fungs model postulates for an elastic response that is independent of, and can be separated from, the temporal response. The experimental results do not show such independence.

An experimental study of biologically inspired artificial skin sensor under static loading and dynamic stimuli

This paper presents an experimental study of the bio-inspired artificial skin consisting of silicone and embedded strain gages, in which silicone imitates the epidermis and dermis, and strain gages mimic corpuscles. The strain gages are embedded in silicone under different configurations like corpuscle in humans skin. Both static displacement and dynamic excitations are applied in arbitrary positions, with different magnitudes and frequencies. The responses are observed by measuring the output signals from strain gages. Comparison with FEM simulation of static displacement shows intuitive agreement. The responses to dynamic excitation in typical frequency range of human somatosensors are obtained both experimentally and with simulation of dynamic modeling. We found that each configuration has advantages and disadvantages. This paper shows how strain gages embedded in silicone will behave in response to both static and dynamic excitations, and suggests modeling and fundamental concepts to design a bio-inspired artificial skin sensor.

Convolutional Neural Network based Estimation of Gel-like Food Texture by a Robotic Sensing System

This paper presents a robotic sensing system that evaluates the texture of gel-like food, in which not only mechanical characteristics, but also geometrical characteristics of the texture are objectively and quantitatively evaluated. When a human chews a gel-like food, the person perceives the changes in the shape and contact force simultaneously on the tongue. Based on their impression, they evaluate the texture. To reproduce this procedure using a simple artificial mastication robot, the pressure distribution of the gel-like food is measured, and the information associated with both the geometrical and mechanical characteristics is simultaneously acquired. The relationship between the value of the human sensory evaluation of the texture and the pressure distribution image is then modeled by applying a convolutional neural network. Experimental results show that the proposed system succeeds in estimating the values of a human sensory evaluation for 23 types of gel-like food with a coefficient of determination greater than 0.92.

Omnidirectional Nonprehensile Manipulation Using Only One Actuator

This paper presents a novel nonprehensile manipulation method that uses the vibration of a plate, where the two degrees of freedom of a part on the plate are controlled by only one actuator. First, a manipulator whose end effector is a flat plate is introduced. By employing an underactuated joint mechanism, the shape and orientation of the vibrational orbit of the plate vary according to frequency and offset angle of the sinusoidal displacement input to an actuator. Then, simulation analyses reveal that the manipulator can omnidirectionally induce translational velocity to the part on the plate. There exists an orthogonality between the effects of the frequency and offset angle on the velocity map of the part. Based on this characteristic, a visual feedback control for manipulating the part is designed. Finally, the proposed method is validated via experiments using a prototype manipulator. A target-trajectory tracking task and a four-way part-feeding task are demonstrated.

Texture evaluation system of paste food by using elastic imitation tongue

This paper presents a texture evaluation system for nursing-care paste foods with a biomimetic approach. To artificially reproduce human oral processing, an elastic imitation tongue is introduced to the compression test device of paste food. During the compression, the tongue is passively deformed and holds a paste sample. Such a tongue behavior varies with respect to characteristics of paste food. Based on this effect, we propose the method for extracting the cohesiveness of paste food by the pressure distribution measurement and the image processing. Then, we develop the texture evaluation system that estimates the value of human sensory evaluation from the feature value of the pressure distribution. The experimental results show that the proposed method can appropriately estimate the value of human sensory evaluation.

Food texture sensing by using an imitation tongue with variable elasticity

This paper proposes a texture sensing system based on a biomimetic approach for nursing-care gel foods. The proposed system is equipped with an imitation tongue that can reproduce the elastic behavior of human tongue. First, we introduce the imitation tongue with a variable elasticity mechanism in the artificial mastication model. In this study, using a prototype of the imitation tongue, we verify that it can reproduce the elasticity of human tongue from the relaxed state to the contracted state. Then, we show that the pressure distribution in the artificial mastication of gel food changes clearly with respect to the elasticity of the imitation tongue. Finally, we develop the texture evaluation system that estimates the values of human sensory evaluation of the texture. We show that the texture can be accurately estimated with the appropriate elasticity of the imitation tongue.