Low-Cost Robot Construction Focused on Educational Environments
Douglas Favaretto
1 a
, Vitor de Assis
1 b
, Dieisson Martinelli
2 c
,
Andre Schneider De Oliveira
2 d
and Vivian Cremer Kalempa
1 e
1
Department of Information Systems, Universidade do Estado de Santa Catarina, S
˜
ao Bento do Sul, Brazil
2
Graduate Program in Electrical and Computer Engineering,
Universidade Tecnol
´
ogica Federal do Paran
´
a, Curitiba, Brazil
Keywords:
Low-Cost Robotics, ROS, Multi-Robot Systems.
Abstract:
Designed for educational environments and motivated by the demand for affordable solutions in robotics. Cost
serves as a limiting factor for the implementation of robotics projects, especially in educational environments
with limited financial resources. By creating a robot composed of simple electronic components, this project
aims to make robotic more accessible, enabling educational institutions to incorporate robotics into their ed-
ucational programs, regardless of their constrained budgets. The robot’s proposed features include the ability
to navigate obstacles and teleoperation, utilizing the ESP8266 for Wi-Fi connectivity, ensuring its operational
versatility. Furthermore, by introducing the robot into an educational environment and interviewing students,
the platform demonstrated the robot as an effective, functional educational tool. Direct evaluations from stu-
dents, contribute to changes and improvements in the platform. It fulfills its purpose of facilitating the learning
of basic concepts in robotics.
1 INTRODUCTION
Mobile robotics is a field that has grown rapidly in
recent years, and many activities and research focus
on the autonomy and capability of robots to perform
different tasks (Arvin et al., 2019). Nevertheless, as
this technology advances, there arises a need to make
it on hand to a broader target audience (Chronis and
Varlamis, 2022). Low-cost robots thus become an im-
portant part of hands-on learning of robotic (Magrin
et al., 2022).
In order to provide researchers with the capabili-
ties and ideas of mobile robotics, this article proposes
the development of a low-cost robot that can be used
as an educational tool This robot is designed to work
with other robots, in order to explore the basic con-
cepts of multi-robot tasks (Feng et al., 2020). Using
this robot, students will gain hands-on experience in
operating and troubleshooting robotic systems.
The proposed robot is equipped with sensors and
a
https://orcid.org/0009-0003-3961-1247
b
https://orcid.org/0009-0007-7022-6135
c
https://orcid.org/0000-0001-7589-1942
d
https://orcid.org/0000-0002-8295-366X
e
https://orcid.org/0000-0001-9733-7352
actuators, which can be programmed to meet their
specific needs. Robots are designed to perform a vari-
ety of tasks, including navigating obstacles (Liu et al.,
2019) and working in collaboration with other robots
to achieve a common goal (Sherwani et al., 2020).The
low-cost nature of the robot make it accessible to a
larger number of educational institutions, allowing
more educational institutions, allowing more students
to take advantage of the educational opportunities of-
fered by robotics.
This paper is organized as follows. In Section II,
the construction of the robot and the use of Robot
Operating System (ROS) in communication between
components and the controller are explained. Section
III discusses the use of a simulator for development as
well as price comparison with other robotic platforms.
Section IV covers the implementation of the low-cost
robot in classrooms and the use of a questionnaire to
assess students’ interest, as well as the results of the
robot implementation Section V covers plans for ex-
panding the robot linup. Finally, Section VI presents
the final considerations.
66
Favaretto, D., de Assis, V., Martinelli, D., Schneider De Oliveira, A. and Kalempa, V.
Low-Cost Robot Construction Focused on Educational Environments.
DOI: 10.5220/0012987500003822
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics (ICINCO 2024) - Volume 2, pages 66-72
ISBN: 978-989-758-717-7; ISSN: 2184-2809
Proceedings Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

2 METHODOLOGY
This section describes in detail the design and con-
struction of the robot as well as a control system using
ROS (Quigley et al., 2009).
This section reviews the main features of the pro-
posed robot and integrates ROS. Divided into three
main parts: controller, mobile base and perception
source, it explores how these components interact to
achieve efficient communication, navigation and en-
vironmental awareness.
2.1 Controller
In the scope of robotics, efficient communication
among different components is crucial for the co-
herent and smart working of the system. The ROS
Noetic, running on Ubuntu 20.04, is the primary tool
used in this project, being a key and widely rec-
ognized software framework for robotics (Blubaugh
et al., 2022).
ROS provides a modular framework for robotics
systems development by providing tools, libraries,
and conventions to simplify programming for robots.
The connection via ROS plays a crucial role. In the
specific context of this project, ROS enables efficient
communication between the controller and the mobile
base through the TCP/IP protocol over a WiFi net-
work.
When initializing the parameters of the mobile
base and specifying the Wi-Fi network to connect to,
along with the IP of the machine running the ROS, a
robust bridge for information exchange is established.
By creating a common environment for communica-
tion enables robot control, transmission of commands
from the controller, and reception of data collected by
the mobile base.
The script provided in Figure 1 is a shell script,
a set of commands in a bash script, used to config-
ure environment variables related to the connection
between the controller and the mobile base. In this
context, the bash script sets up two specific environ-
ment variables. ROS MASTER URI is responsible
for specifying the URL of the ROS Master. ROS
Master is a core component that manages coordina-
tion and communication among the various nodes,
which are the processes that constitute the ROS sys-
tem. The value allocate to ROS MASTER URI is
“http://xxx:11311/”, specifying that the ROS Master
is find on a system with the IP address “xxx” and on
port 11311.
Other variable is ROS IP, used to specify the
IP address that the ROS system should employ to
communicate with other systems. This is particu-
Figure 1: Shell script to connect multiple machines.
larly relevant in network scenarios where the system
has multiple network interfaces. In the case of this
script, ROS IP is set to the same IP address as the
ROS MASTER URI.
These configurations are crucial to ensure effec-
tive communication among the nodes. By explic-
itly setting the ROS master and the IP address to be
used, the Figure 1 enables the system to operate prop-
erly on a specific network. It is sufficient for the
operator, upon opening a new terminal, to call the
“conecta lena” function to establish the connection
with the mobile base, facilitating interaction with it.
2.2 Mobile Base
The mobile base is equipped with the WeMos D1 pro-
totyping board based on the ESP8266 chip, which
features a 32-bit microcontroller. This microcon-
troller, specifically the Xtensa LX106, operates at a
clock speed of 80 MHz, offering sufficient process-
ing power for various IoT applications. Addition-
ally, it includes built-in Wi-Fi capabilities, making it
ideal for projects that require wireless communication
(Macheso and Meela, 2021).
The microcontroller has 4 MB of Flash memory,
64 KB of instruction RAM, and 96 KB of data RAM,
providing adequate memory for running complex
tasks. Designed to be a low-cost, user-friendly Inter-
net of Things (IoT) development board, the ESP8266
is known for its ability to connect to Wi-Fi networks
and its low power consumption, making it a versa-
tile component for a wide array of embedded systems
(Budiharto et al., 2021).
The WeMos D1 board has a central role in the
project, acting as the main controller for the mo-
bile base. Its compatibility with the Arduino plat-
form simplifies programming using the Arduino IDE,
leveraging features and support from the existing
community (Pe
˜
na, 2020).
To control the robot’s behavior, code was devel-
oped in the Arduino IDE. This code enables the def-
inition of which parts of the system will be responsi-
ble for sending and receiving messages. Specifically,
it configures communication with the infrared sensor,
the mobile base motors, and the controller.
In the context of the motors, a callback function
named “odometry cb” was implemented. This func-
tion handles messages related to the robot’s velocity,
calculating and controlling the motor speeds based on
Low-Cost Robot Construction Focused on Educational Environments
67

the received instructions. This approach enables the
robot to respond appropriately to motion commands
by converting odometry information into signals un-
derstandable by the motors.
To better integrate these components, the WeMos
D1 board is equipped with a shield, reducing the
need to connect a large number of wires between
them. Additionally, the robot’s power is supplied by
a 10000mAh power bank, connected to the board.
Additionally, the robot’s was designed using
SketchUp Online, a free tool, requiring minimal effort
for learning (Chiodi and de Figueiredo, 2021). The
fully assembled robot is shown in Figure 2.
Figure 2: Mobile Base.
Regarding the fabrication of the parts, a GT-
Max3D 3D printer, model A2V2, was utilized, em-
ploying ABS material in green.
2.3 Source of Perception
The Sharp GP2Y0A41SK0F distance sensor was in-
corporated as the perception source, as can be seen in
Figure 3. This sensor employs an infrared light mea-
surement principle, emitting a beam of light towards
the object (Siyal et al., 2021).
This sensor is constituted by the combination of a
Position Sensitive Detector (PSD), a device that mea-
sures the position of a point of light or incident radi-
ation on its surface. It typically consists of an array
of photodiodes, the PSD provides information about
the position of the incident light, allowing its appli-
cation in tracking, positioning, and control of optical
devices.
An Infrared Emitting Diode (IR-LED) is a type of
semiconductor diode designed to emit infrared light.
They are commonly utilized in remote controls de-
vices. They operate by emitting infrared light when
an electric current passes through them.
Figure 3: Source of Perception.
The sensor can provide information about the dis-
tance between itself and the target object. The IR-
LED emits infrared light, which reaches the object
and is reflected, captured by the PSD, as depicted in
Figure 4. The resulting signal is then processed by a
circuit that converts the distance into a voltage varia-
tion.
Figure 4: Infrared Sensor functioning.
To increase the sensor’s perception range, it was
mounted on top of the robot’s structure, connected to
a servo motor. The servo motor used is an MG90S,
ideal for robotics projects or radio-controlled models.
With the addition of the servo, it became possible to
expand the robot’s spatial perception from a single po-
sition to a total of 180 positions.
In the code that establishes the relationship
between the Sharp Infrared (IR) sensor and the
servo motor, was included the “SharpIR” library,
which provides specific functionalities for work-
ing with Sharp sensors. The creation of an ob-
ject called “SharpSensor” to represent the sensor.
The “SharpSensor” object is configured for the
“GP2Y0A41SK0F” model and is connected to analog
pin A0.
Additionally, a topic named “topic sharp” is es-
tablished to facilitate communication between system
components. A publisher is configured to send infor-
mation from the sensor to this topic, enabling the ef-
ficient integration of these data across different parts
of the project.
Similar to the infrared sensor, an object named
’servo’ is created to represent the control of the servo
motor. The variable ’topic servo’ identifies the topic
related to servo control in ROS. This topic is associ-
ated with a callback function responsible for control-
ling the servo motor based on the received messages.
The servo callback function is triggered when a
message is received on the servo topic. This message
contains data representing the desired angle for the
servo motor. A function is then employed to adjust the
servo’s position based on the information contained in
the message.
This strategy provides a solution to emulate func-
tionalities similar to those of a LIDAR sensor, en-
ICINCO 2024 - 21st International Conference on Informatics in Control, Automation and Robotics
68

abling the robot’s controller to make informed de-
cisions based on distance readings (Li and Ibanez-
Guzman, 2020). The sensor/servo combination
makes a solution for acquiring data related to the
robot’s spatial perception, allowing more adaptive in-
teraction with the surroundings.
3 COST ANALYSIS AND
SIMULATION
The development prioritized affordability, by utilizing
components available in the Brazilian market. The
costs incurred can be observed in Table1.
Table 1: Components Cost.
Description Prices
Micro Servo Motor $ 4,70
Sensor IR Sharp Gp2y0a21 $ 7,43
Power Bank $ 12,40
Jumper Cables $ 2,22
H Bridge $ 3,14
3D printer Filament $ 3,06
WeMos D1 Board $ 10,91
Shield $ 2,68
4 DC Motors Kit $ 11,09
Total $ 57,64
The total cost, as shown in Table 2, demonstrates
a savings of approximately 55% compared to Mona
and 66.85% compared to FOSSBot.
Table 2: Price Comparison with Other Robotic Platforms.
Robot Price
Developed Robot $ 57,64
Mona $ 128,00
FOSSBot $ 200,00
The cost-benefit analysis was based on the com-
parison of prices with other robotic platforms such
as FOSSBot (Chronis and Varlamis, 2022) and Mona
(Arvin et al., 2019), both focus on simplified con-
struction and reduced costs for the widespread pro-
motion of robotics studies, these comparison reveals
a significant advantage for the developed robot.
The cost analysis provides a quantitative assess-
ment, but it is also important to consider the perfor-
mance provided by the robot, emphasizing its effi-
ciency and viability.
Simultaneously, the application of the Cop-
peliaSim environment, formerly known as V-REP
(Rohmer et al., 2013), a widely used platform for
robotic simulation, enabling modeling and simulation
of robot behavior in virtual environments.
For example, (Montenegro et al., 2022) developed
a spherical robot that has only a single point of contact
with the ground. The robot moves using joints, axes,
counterweights, and a pendulum. The CoppeliaSim
simulator was used to conduct a series of simulations
regarding the robot’s behavior.
Similarly, (Chakraborty and Aithal, 2021) ex-
plored the potential of CoppeliaSim to develop a
robotic arm with the purpose of facilitating robotics
research. The authors emphasize two main problems:
the high cost of real robots and the potential risks in-
volved in testing real robots due to bugs or abnormal
activities that could result in damage to property, risks
to human life, or harm to the robot itself.
Additionally, a simulated version was developed
in the CoppeliaSim environment, as shown in Figure
5. The configuration and operation of the robot in the
simulator mirror those of the real robot, incorporating
the same methods of information exchange between
the mobile base and the controller.
Figure 5: Simulated robot in CoppeliaSim.
This approach, as evidenced by previous studies,
enables the simulation of techniques before imple-
mentation on the physical robot, providing a safe and
efficient space for virtual testing. This approach not
only facilitates the understanding of the robot’s ca-
pabilities but also underscores the versatility of Cop-
peliaSim as an essential tool in the development and
enhancement of various robotic applications.
4 CLASSROOM APPLICATION
The low-cost robot was incorporated into two courses
in the Bachelor of Information Systems program at
the Universidade do Estado de Santa Catarina in the
Centro de Educac¸
˜
ao do Planalto Norte (UDESC CE-
PLAN): Special Topics I and Special Topics II. In
these courses, students used their machines to connect
to the robot, as demonstrated earlier.
The proposed activity consisted of two main
stages. In the first stage, the students developed a
teleoperation system that allowed remote control of
the robot through manual commands. This phase was
Low-Cost Robot Construction Focused on Educational Environments
69

Figure 6: Questionnaire Results.
used to help students understand the basic principles
of robot movement and control.
In the second stage, the focus shifted to the im-
plementation of an obstacle avoidance system. The
students were challenged to develop an algorithm ca-
pable of autonomously detecting and avoiding obsta-
cles using the Sharp sensor to identify obstacles and
adjust the robot’s trajectory as needed. This phase
aimed to introduce advanced robotics concepts, such
as environmental perception and decision-making.
With the aim of evaluating the level of interest of
the students in working with the robot, a question-
naire consisting of 9 questions was manege after the
classes. Five questions were open-ended, seeking the
students’ opinions, while four were based on the Lik-
ert Scale.
The Likert scale is commonly used in quantitative
visualization. According to (Bertram, 2007), Likert
scales are a measurement method that does not in-
volve comparisons and focuses on a single dimension.
Participants has to express their degree of agreement
with a statement. These scales are designed to assess
the intensity of opinion or attitude regarding a single
topic.
The implementation of the robot in the classroom,
followed by the questionnaire administered, revealed
a variety of perceptions, as shown in Figure 6. The
graph displays a scale from 0 to 100, depicting the stu-
dents’ opinions regarding the formulated questions. It
was possible to gather feedback from the students and
understand their opinions and the benefits that the use
of the robot brings to professional development.
The Likert scale questions made it possible to
evaluate how well the lesson achieved the objective
of using the robot, the difficulties encountered, the
advantages of using the robot, and the development
of specific skills.
In terms of achieving the objectives, the students
expressed that the results were attained, as exem-
plified in Figure 6, with predominantly positive re-
sponses. The difficulty of the class was mostly con-
sidered moderate or easy, indicating a relative acces-
sibility of the technology.
Regarding perceived benefits include the conve-
nience of transportation and the chance to engage
with an actual robot for experimentation without any
associated risks. The relevance of low cost in tech-
nology dissemination was acknowledged, emphasiz-
ing the potential for inclusion across different social
classes.
Some challenges were identified, such as adapting
values between simulator and real robot, the robot’s
adherence to the floor, and the lack of documentation
to maximize the robot’s possibilities. These compar-
ative study highlights the effectiveness of affordable
robotics for use in education, identifying accessibil-
ity, benefits and challenges to be addressed.
5 FUTURE PROJECTS
For future projects, this initiative opens up the pos-
sibility of expanding the robot lineup by introducing
specialized variants and more advanced models. Ex-
ploring the integration of 3D cameras and LIDAR and
more powerful actuators, enhancing the robot’s abil-
ity execute specific tasks.
Furthermore, artificial intelligence and machine
learning technologies will offer new possibilities for
the autonomy and interaction of robots. These ad-
vances will provide access to cutting-edge technolo-
gies.
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70

6 CONCLUSION
This work introduced the conception and construc-
tion of a low-cost robot designed for educational use
in classrooms and research, focusing on learning and
applying essential concepts in mobile robotics on a
simple platform. The robot, composed of accessible
components, provides an economical alternative for
institutions, enabling the exploration of various tasks
and scenarios in the field of robotics.
The methodological approach adopted involved a
detailed explanation of the three main parts and their
components: the Controller, the Perception Source,
and the Mobile Base. The use of ROS facilitated
communication between these components, while the
CoppeliaSim expanded possibilities before applica-
tion to the real robot.
In practical application in university courses, the
robot demonstrated its feasibility in aiding the teach-
ing and understanding of robotics concepts. The cost
evaluation revealed its financial advantage for insti-
tutions with limited budgets compared to other plat-
forms. The creation of a simulated version of the
robot complemented the hands-on experience, pro-
viding a safe environment before implementation on
the physical robot.
Moreover, the implementation of the robot in uni-
versity courses not only confirmed its utility as an ed-
ucational tool but also highlighted its ability to adapt
to different levels of complexity and areas of study.
This includes basic introduction to robot program-
ming to more complex tasks.
In conclusion, the development of the low-cost
robot contributes significantly to robotics by provid-
ing an affordable and practical solution. Its applica-
tion in the classroom, along with simulation in Cop-
peliaSim, demonstrates its utility and versatility. The
combination of affordable materials and the potential
to expand knowledge in robotics emphasizes the im-
portance of this innovation for both educational and
scientific applications
ACKNOWLEDGEMENTS
The project is supported by the National Council for
Scientific and Technological Development (CNPq)
(process CNPq 407984/2022-4); the Fund for Sci-
entific and Technological Development (FNDCT);
the Ministry of Science, Technology and Innovations
(MCTI) of Brazil; the Araucaria Foundation; and the
General Superintendence of Science, Technology and
Higher Education (SETI).
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