Chikara Nagai

Which Robot Features Can Stimulate Better Responses from Children with Autism in Robot-Assisted Therapy?

This study explores the response of autistic children to a few design features of the robots for autism therapy and provides suggestions on the robot features that have a stronger influence on the therapeutic process. First, we investigate the effect of selected robot features on the development of social communication skills in autistic children. The results indicate that the toys “face” and “moving limb” usually draw the childrens attention and improve childrens facial expression skills, but do not contribute to the development of other social communication skills. Secondly, we study the response of children with low-functioning autism to robots with verbal communication functionalities. Test results show that children interacted with the verbal-featured robot more intensively than with the experimenter. We conclude that robots with faces and moving limbs can engage autistic children in a better way. Facial expression of the robots can elicit a greater response than prompting by humans.

Vision-Based Tactile Sensing and Shape Estimation Using a Fluid-Type Touchpad

In this paper, we propose a new method to estimate the shape and irregularity of objects by a vision-based tactile sensor, which consists of a CCD camera, LED lights, transparent acrylic plate, and a touchpad which consists of an elastic membrane filled with translucent red water. Intensities of red, green and blue bands of the traveling light in the touchpad are analyzed in this study to estimate the shape/irregularity of the object. The LED light traveling in the touchpad is scattered and absorbed by the red pigment in the fluid. The depth of the touchpad is estimated by using the intensity of the light obtained from the red-green-blue (RGB) values of the image, in consideration of the scattering and reflection effects. The reflection coefficient that depends on the shape of the membrane, was decoupled in the proposed formulation. The intensity of the traveling light is represented with the geometrical parameters of the touchpad surface. In order to reduce the approximation error caused by unmodeled factors, we compensate the error by using a function of the deformation of the membrane. The validation of the proposed method is confirmed through experimental results.

Contact State Estimation by Vision-based Tactile Sensors for Dexterous Manipulation with Robot Hands Based on Shape-Sensing

We propose a new method for estimating the contact state of objects with varying shapes on a vision-based fluid-type tactile sensor, which touch pad is an elastic transparent membrane of silicon rubber with dotted pattern printed on its inner side. The membrane is filled with translucent red colored water. The proposed method leads to better understanding of the objects shape and movement, and can be applied for accomplishing reliable and dexterous handling tasks by robot hands.

Shape sensing by vision-based tactile sensor for dexterous handling of robot hands

In this paper, we propose a new method to estimate the shape and irregularity of objects by the vision-based tactile sensor, which is consist of a CCD camera, LED lights, transparent acrylic plate, and the touch pad which consists of the elastic membrane of silicon rubber and the translucent red water filling inside of the membrane. Intensities of red, green and blue bands of the lights are focused to estimate the shape of the object and the irregularity of the object surface. The LED light traveling in the translucent touch pad is scattered and absorbed by the particles of the red pigment which fill the inside of the touch pad. The depth of the pad is estimated by using the intensity of the light obtained from the red-green-blue (RGB) values in the image, in consideration of the scattering and reflection effects. The intensity of traveling light decays depending on the depth of the pad, the reflection coefficient to the membrane of the pad surface, the scattering coefficient of the pigment particle, and so on. The reflection and scattering coefficients that are considered very hard to obtain, are decoupled in the proposed formulation, and the intensity of traveling light is represented with the function of the geometrical parameters of the pad surface. In order to decrease the approximation error caused by unmodeled factors, the compensation is made by using the function of the shape of the membrane. The usefulness of the proposed method is confirmed through the experimental results. The shape sensing method is developed for dexterous handling by robot hands.

Enhancement of the Communication Effectiveness of Interactive Robots for Autism Therapy by Using Touch and Colour Feedback

Abstract Previous studies in the field of robot assisted therapy demonstrated that robots engage autistic children’s attention in a better way. Therefore, the interactive robots appear to be a promising approach for improving the social interaction and communication skills of autistic children. However, most of the existing interactive robots use a very small number of communication variableswhich narrow their effectiveness to a few aspects of autistic childrens’ social communication behaviour. In the present work, we explore the effects of touching and colours on the communication effectiveness between a robot and an autistic child and their potential for further adjustability of the robot to child’s behaviour. Firstly, we investigated touching patterns of autistic and non-autistic children in three different situations and validated their responses by comparison of touching forces. Results showed that patterns of touching by non-autistic children have certain consistency, while reaction patterns in autistic children vary from person to person. Secondly, we studied the effect of colour feedback in autism therapy with the robot. Results showed that participants achieved better completion rate when colour feedback was provided. The results could support the design of more effective therapeutic robots for children with autism.

A Preliminary Study on the Response of Autistic Persons to a Robot Feedback based on Visual Stimuli

Abstract Interactive robots are seen as an efficient tool for the improvement of the social communication skills of autistic children. Recent studies show that the effectiveness of the human-robot interaction can be improved further if the robot can provide positive feedback to the child when he/she demonstrates behaviour or social skills as expected. However, there is no clear answer to which visual stimuli and which combination of visual stimuli could attract better attention. In this paper we present initial results from our study of the response of participants with autism traits to four visual stimuli. We conducted a series of experiments where the experimental system provided a visual response to the user’s actions and monitored the user’s performance for each visual stimulus. The experiments were organised as a game and included four groups of participants with different levels of autism. The results showed that a colour tended to be the most effective way for robot interaction with autistic people. The results could help the design of very effective assistive robots for supporting people with autism.

Investigation of human mirror-image for bilateral movement training of upper limb rehabilitation

Bilateral movement training for the upper extremity rehabilitation is attracting a lot of attention. In this paper, we investigated the relationship between left and right of the human body system(human mirror-image) using robotic force field for planning effective bimanual movement training of upper limb rehabilitation. We use two robot manipulators and force/torque sensors to realize the force field, and we verify that the bimanual movement is better than unimanual, and how coordinate system of task and force field affect to the bimanual movement through the experiment.

Simulation of human walking with powered orthosis for designing practical assistive device

To design a powered assistive orthosis for human walking, we have simulated walking motion with an orthosis. The model dynamics of the coupled human-orthosis is represented by a 10-rigid-link system. In this model there exist rotational joints at lumbar, both thighs and both legs for orthosis, and each joints are controlled by a couple of central pattern generators (CPG) which imitates neuronal system in the spinal cord of mammals. The CPG controller modeled by 18 oscillators which have the sensory feedbacks and generates the joint torques to move the skeletal model of the coupled human-orthosis. This means that we use five actuators for controlling orthosis in the both of sagittal and frontal plane. The parameters of the CPG and the connecting gains are optimized by using a genetic algorithm. We have achieved the successful simulation of stable walking against disturbances with this model. The simulation results indicate the possibility of a practical assistive orthosis with five active joints for stable walking.

Acquisition of tactile information by vision-based tactile sensor for dexterous handling of robot hands

In this paper, we propose a new method for calculation of the contact region and the location of an object from the data acquired from vision-based tactile sensor, which touch pad is an elastic transparent membrane of silicon rubber with dotted pattern printed on its inner side. The membrane is filled with translucent red colored water. The algorithm for calculation of the contact region is based on the curvature radius of the elastic membrane and considerations of the conditions for balance between the tensional forces of the membrane and the inner pressure. The location of the object is calculated from the relations between the translational displacement of the object and the displacement of the contacting dots. The rotation angles of the object are estimated from the rotation matrix of the three basis vectors by accumulating changes of the rotation angles of the rotation matrix for applying to the object rolling on the sensor. This paper also provides some experimental results that demonstrate the usefulness of the proposed method. Proposed method can be applied in many robot tasks that require dexterity of the robot hands.

Evaluation of bilateral transfer characteristics based on virtual impairment

Bilateral movement training based on robot-aided rehabilitation systems has been attracting a lot of attention as a post-stroke motor rehabilitation protocol. In this paper, we investigate the effects of different conditions which were imposed on the unimpaired upper extremity to find exact therapeutic conditions for planning more appropriate bilateral movement training. Active/passive, loaded/non-loaded, and unimanual/bimanual movements were used as the experimental conditions. Twenty subjects were randomly assigned to one of four groups, namely the passive group(PG), the active non-load group(ANLG), active load group(ALG), and the control group(CG) and were asked to perform tasks with their left upper extremity with respect to the conditions. The comparison results revealed that the active loaded group showed the recovery time from adaptation was faster than another groups.