Therapeutic-assisted robot for children with autism

In this paper, we propose a therapeutic-assisted robot for children with autism to ameliorate their skill of joint attention. The robot conducts a goal-directed based interaction to establish engagement between the child and robot in order to establish a beneficial learning environment for autistic children. An unsupervised Mixture Gaussian-based cluster method is proposed to detect the child's intention in real time to process the goal-directed task smoothly. The novelty of this approach is that does not require the use of any training data or a trained model to detect the child's intention. Our autonomous robotic system is tested with several autistic children at a School for the Disabled in Nagoya, Japan. The results of the initial interaction showed that the children enjoyed interaction with and feedback from the robot, which confirmed that the robot can be used as mediator or an object of joint attention. The unsupervised approach was able to detect the children's intention at every time segment to process the goal-directed task with a higher accuracy rate. The results of the goal-directed task showed that the proposed interaction was highly effective in enhancing their joint attention. Since most of the children attempted to imitate the robot's gestural behaviors and used a variety of learning patterns to attend to the robot's fingered object in the environment to obtain joint attention with robot.