Implementation of Ichiro Teen-Size Humanoid Robots For Supporting Autism Therapy
Abstract
The humanoid robot is a robot which has humanlike
shapes and/or functions. For instance, a humanoid robot has
a neck that connect the head to the body, two legs to support
the body, and has two arms on the right- and left-side of its
body. According to the RoboCup competition, the humanoid robot
can be classified into several types based on their sizes, i.e.,
kid-size, teen-size, and adult-size. In this study, we developed
a teen-size humanoid robot with the aim of approaching the
size of children’s bodies with autism to facilitate the interactions
between the robot and the children. In general, the autism person
is difficult to communicate with a normal person because there is
a virtual wall that limits the world of the autism with the normal
person. As long as the wall is standing upright, communication
will be difficult, so that inconvenience occurred on both sides.
Especially in children, the process learning will be hampered if
communication is blocked. In many cases, the autism children
more actively interact and/or communicate with objects such as
books, toys, and so forth. This motivated us to use a humanoid
robot as a mediator of interactions and/or communication with
the autism to support their therapy. Of course the choice of
humanoid robots must also be considered both financially and
functionally. At present there are many commercial humanoid
robots such as: NAO, Darwin-OP, and so forth. However, the
price offered is relatively expensive and also inflexible capabilities
because existing hardware and software can no longer be freely
developed. Flexibility in hardware and software is very important
for the implementation of a system that can be used in supporting
the therapy for autism. These facts motivated us to develop the
Ichiro teen-size robot. In this study, we developed a therapy for
autism in the form of movement by humanoid robots such as
a gymnastic movement. The movement is expected to be able
to be followed by the autism and has a positive impact on
therapy. One of the advantages of this study is being able to
add robot movement flexibly, so that the movements suggested
by psychiatrists should be able to be implemented and help to
support the autism.
Keywords: humanoid robots, RoboCup, robot's movements, therapy for children autisms.
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PDFReferences
https://www.robocup.org/
NAO robot: https://www.softbankrobotics.com/emea/en/robots/nao.
Darwin-OP: https://en.wikipedia.org/wiki/DARwIn-OP.
IGUS: http://www.nimbro.net/OP/.
Berns K., Asfour T., Dillmann R. (2000) Design and Control of the
Humanoid Robot ARMAR. In: Morecki A., Bianchi G., Rzymkowski
C. (eds) Romansy 13. International Centre for Mechanical Sciences
(Courses and Lectures), vol 422. Springer, Vienna.
M. Attamimi, T. Araki, T. Nakamura, and T. Nagai, “Visual Recognition
System for Cleaning Tasks by Humanoid Robots,” International Journal
of Advanced Robotic Systems, Vol. 10, No. 11, pp. 114, 2013.
A Di Nuovo, D Conti, G Trubia, S Buono, S Di Nuovo, “Deep learning
systems for estimating visual attention in robot-assisted therapy of
children with autism and intellectual disability,” Robotics 2018.
Ryoma Hida, Tetsuji Yamada, Masahiro Miyata, Takashi Omori, “De-
velopment of Interest Estimation Tool for Effective HAI,” Proceedings
of the Fifth International Conference on Human Agent Interaction, pp.
-486.
Muhammad Attamimi, Masahiro Miyata, Tetsuji Yamada, Takashi
Omori, Ryoma Hida, “Attention Estimation for Child-Robot Interac-
tion,” Proceedings of the Fourth International Conference on Human
Agent Interaction, pp. 267-271.
Pepper robot: https://www.softbankrobotics.com/us/pepper.
Max Schwarz, Julio Pastrana, Philipp Allgeuer, Michael Schreiber,
Sebastian Schueller, Marcell Missura and Sven Behnke: Humanoid
TeenSize Open Platform NimbRo-OP In Proceedings of 17th RoboCup
International Symposium, Eindhoven, Netherlands (2013).
Julien Allali, Louis Deguillaume, Remi Fabre, Loic Gondry, Ludovic
Hofer, Olivier Ly, Steve NGuyen, Gregoire Passault, Antoine Pirrone,
and Quentin Rouxel. Rhoban Foot-ball Club: RoboCup Humanoid Kid-
Size 2016 Champion Team Paper, pages 491502. (2017).
8. Muhammad Arifin, Muhammad Ardi Pradana, Uti Solichah, Satria
Hafizhuddin, Rizal Hafidhilllisan, Dhany Satrio Wicaksono, Muhammad
Reza Ar Razi, Rudy Dikairono Mu-htadin, ICHIRO Kid-Size 2016
Team Description Paper. (2016).
T. Ojala, M. Pietikainen and T. Maenpaa, ”Multiresolution gray-scale
and rotation invari-ant texture classification with local binary patterns,”
in IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol. 24, no. 7, pp. 971-987, (2002).
Paul Viola and Michael J. Jones. Rapid Object Detection using a
Boosted Cascade of Sim-ple Features. In IEEE Computer Vision and
Pattern Recognition CVPR, (2001).
Rainer Lienhart and Jochen Maydt. An Extended Set of Haar-like
Features for Rapid Ob-ject Detection. IEEE ICIP 2002, Vol. 1, pp. 900903,
Sep.
(2002).
A. Howard. Mobilenets: Efficient convolutional neural networks for
mobile vision applica-tions, arXiv preprint arXiv:1704.04861, (2017).
DOI: https://doi.org/10.12962/j25796216.v3.i1.75
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