Abstract
In this paper, we report the effectiveness of a therapeutic humanoid robot for children with autism to improve his/her imitation skill. In order to realize this system, a robot has to provide two functions: mimicking and evaluating the child’s motion in real time. The former function is achieved by selecting key frames using the Q-Learning approach to remove noisy camera data. The latter is established via a cluster-based framework on Mixture Gaussian and Expectation-Maximization algorithm using parameters which are converted by Principal Component Analysis. Practical experiments are shown in which autistic children interact with a robot and are trained by executing specific tasks for improving imitation skill.
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Fujimoto, I., Matsumoto, T., De Silva, P.R.S., Kobayashi, M., Higashi, M. (2010). Study on an Assistive Robot for Improving Imitation Skill of Children with Autism. In: Ge, S.S., Li, H., Cabibihan, JJ., Tan, Y.K. (eds) Social Robotics. ICSR 2010. Lecture Notes in Computer Science(), vol 6414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17248-9_24
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DOI: https://doi.org/10.1007/978-3-642-17248-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17247-2
Online ISBN: 978-3-642-17248-9
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