Citation: Singh, A.; Raj, K.; Kumar, T.;
Verma, S.; Roy, A.M. Deep
Learning-Based Cost-Effective and
Responsive Robot for Autism
Treatment. Drones 2023, 7, 81.
https://doi.org/10.3390/
drones7020081
Academic Editor: Diego
González-Aguilera
Received: 17 November 2022
Revised: 7 January 2023
Accepted: 15 January 2023
Published: 23 January 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Deep Learning-Based Cost-Effective and Responsive Robot for
Autism Treatment
Aditya Singh
1,
*, Kislay Raj
2
, Teerath Kumar
2
, Swapnil Verma
3
and Arunabha M. Roy
4,
*
1
Center of Intelligent Robotics, Indian Institute of Information Technology, Allahabad 211015, India
2
SFI for Research Training in Artificial Intelligence, Dublin City University, D09 Dublin, Ireland
3
United Kingdom Atomic Energy Authority, Abingdon OX14 3DB, UK
4
Aerospace Engineering Department, University of Michigan, Ann Arbor, MI 48109, USA
* Correspondence: rsi2018003@iiita.ac.in (A.S.); arunabhr.umich@gmail.com (A.M.R.)
Abstract:
Recent studies state that, for a person with autism spectrum disorder, learning and improve-
ment is often seen in environments where technological tools are involved. A robot is an excellent
tool to be used in therapy and teaching. It can transform teaching methods, not just in the classrooms
but also in the in-house clinical practices. With the rapid advancement in deep learning techniques,
robots became more capable of handling human behaviour. In this paper, we present a cost-efficient,
socially designed robot called ‘Tinku’, developed to assist in teaching special needs children. ‘Tinku’
is low cost but is full of features and has the ability to produce human-like expressions. Its design is
inspired by the widely accepted animated character ‘WALL-E’. Its capabilities include offline speech
processing and computer vision—we used light object detection models, such as Yolo v3-tiny and
single shot detector (SSD)—for obstacle avoidance, non-verbal communication, expressing emotions
in an anthropomorphic way, etc. It uses an onboard deep learning technique to localize the objects
in the scene and uses the information for semantic perception. We have developed several lessons
for training using these features. A sample lesson about brushing is discussed to show the robot’s
capabilities. Tinku is cute, and loaded with lots of features, and the management of all the processes is
mind-blowing. It is developed in the supervision of clinical experts and its condition for application
is taken care of. A small survey on the appearance is also discussed. More importantly, it is tested on
small children for the acceptance of the technology and compatibility in terms of voice interaction. It
helps autistic kids using state-of-the-art deep learning models. Autism Spectral disorders are being
increasingly identified today’s world. The studies show that children are prone to interact with
technology more comfortably than a with human instructor. To fulfil this demand, we presented
a cost-effective solution in the form of a robot with some common lessons for the training of an
autism-affected child.
Keywords: autism therapy; computer vision; robot–child interaction; robot design; robot vision
1. Introduction
Deep learning (DL) algorithms have shown promising results in the range of domains,
such as images [
1
–
10
], audio [
11
–
16
], text [
17
,
18
], object detection [
19
–
21
], brain–computer
interface [
22
–
24
], and across diverse scientific disciplines [
25
,
26
]. Robotics can utilize a
combination of these domains and it can transform the way of living life. It has already been
impacting many areas of our lives, and one of that areas is education. By the addition of
deep learning models to robot functions, robots can make learning more practical, exciting,
and fun [
27
]. It is one of the advanced and interdisciplinary tools in STEM education [
28
].
There are many commercial robots available in the market to teach programming, math-
ematics, sensor technology, mechanics, and electronics, among many other things [
29
].
The ease of learning has also increased with the contribution of open-source, low-cost,
easy-to-use tools, such as single-board computers and micro-controllers. Learning through
Drones 2023, 7, 81. https://doi.org/10.3390/drones7020081 https://www.mdpi.com/journal/drones
