EAI Endorsed TransactionsPreprint Edu-Rover: Application of

Edu-Rover: Application of Unmanned Vehicle

Systems for Robotics and STEM Education in Nigeria

Mbadiwe Samuel Benyeogor

1,2,∗

, Oladayo Olufemi Olakanmi

, Kosisochukwu Pal Nnoli

, and

Mohammed Chonoko Gwani

Automata Research Group (ARG), Arvin Instruments Limited, Lagos, Nigeria

Department of Electrical and Electronic Engineering, University of Ibadan, Ibadan, Nigeria

Department of Physics, Kebbi State University of Science and Technology, Aliero, Nigeria

Abstract

INTRODUCTION: Robotics needs to be made simple to understand in order to serve as a direct introduction

to programming. In this paper, we propose the Edu-Rover (an unmanned vehicle system) for teaching robotics,

and other science, technology, engineering, and mathematics (STEM) related subjects.

OBJECTIVES: The aim of this project is to expose students to the applications of the theoretical knowledge

learned in STEM subjects.

METHODS: To determine the applicability of our apparatus, we conducted workshops in schools. These

include the collection of questionnaire data from students and teachers to evaluate its pedagogical

signiﬁcance.

RESULTS: Results show that our Edu-Rover is useful for teaching STEM subjects and concepts in schools.

CONCLUSION: Thus, we hope that this would stimulate creativity and cognitive abilities among students,

especially in developing countries like Nigeria, in robotics and other STEM related subjects.

Received on 17 January 2021; accepted on 12 February 2021; published on 17 February 2021

Keywords: Edu-rover, internet of things, instructional apparatus, tele-operation, STEM education, robotics.

Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so

long as the original work is properly cited.

doi:10.4108/eai.17-2-2021.168719

1. Introduction

Robotics is an interdisciplinary ﬁeld of a broad-based

education that cuts across diﬀerent ﬁelds of science and

engineering, and even non-technical ﬁelds like creative

art and psychology. According to [1], robotics is primar-

ily the technology and the underlying science that inte-

grates Physics, Mathematics, Mechanical Engineering,

Electrical Engineering, and Computer Science with the

goal of re-engineering and automating some aspects of

human functions, especially the mobility and manip-

ulative functions of the animal. The replication of our

biological locomotive features as transport machines

has intrigued the imagination of many young minds;

as a result, this art of bio-mimicry has inspired the

ﬂair of these people for Science, Technology, Engineer-

ing, and Mathematics (STEM). Based on this insight,

∗

Corresponding author. Email: [email protected]

many educational systems around the world are tak-

ing practical steps to reform their STEM education

from early childhood to college-level studies, mainly

through increased eﬀorts to incorporate new technolog-

ical and project-based learning activities [2]. According

to [3], this approach could enhance the students’ ability

to grasping advanced technological concepts (such as

mechatronics and programming) that are intrinsically

part of robotics.

In the United States, policy makers and educators

predict the shortage of workers in STEM ﬁelds and

are concerned that this will have a negative impact

on the economy [4]. For this reason, many American

schools are introducing STEM-related subjects, study

programs, and extracurricular hands-on activities

into their educational system. A typical example

of this initiative is the FIRST robotics competition

(FRC); where ‘FIRST’ stands for “For Inspiration and

Recognition of Science and Technology”. The FRC is

an international sport-oriented high school robotics

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competition founded by Dean Kamen and Woodie

Flower in 1992. Every year, FRC sponsors teams of high

school students, instructors, and mentors to work for a

duration of six-week to develop game-playing robots

[5]. Since its inception, FRC has contributed to deﬁning

America’s path to space exploration [6]. This is evident

in the success story of space robots and planetary

rovers like the opportunity, spirit, and curiosity that

has enabled scientists in NASA to probe extraterrestrial

environments like the surface of the moon and

planet Mars [7]. In Nigerian secondary education,

the major STEM subjects include Basic Science, Basic

Technology, Computer Studies, Mathematics, Physics,

Technical Drawing, Auto-mechanics, Chemistry, and

Biology. There is hardly a practicable didactic means

of establishing a unifying relationship between these

STEM subjects. The only subject that promises this kind

of synergism is Robotics. This instructional constraint

is also palpable in our universities and polytechnics,

where the relevant faculties are struggling to modify

science and engineering curricula to conform to world

best practice, which is largely driven by advances in

automation, robotics, and artiﬁcial intelligence (AI).

Unfortunately, several infrastructural factors are

hindering the full introduction of robotics in Nigeria’s

educational system. These include the epileptic supply

of electric power, shortage of indigenous robot makers,

poorly equipped or total lack of robotics laboratory in

secondary schools. This is very evident in the report

of [8] on the opinion of stakeholders that Nigeria is

not prepared for robotics education. However, some

prominent Nigerians have expressed optimism on the

capability of adopting and nurturing robotics education

in Nigeria. A Nigerian former Education Minister, Dr.

Obiageli Ezekwesili while calling for a radical change

in the Nigerian education sector in Lagos [9] has

charged the federal government of Nigeria to focus on

key reforms that will bring about the introduction of

novel technological contents like artiﬁcial intelligence,

robotics, internet of things and machine learning into

Nigerian schools’ curricula. In recent times, some

foreign agencies in collaboration with the Nigerian

government and some indigenous entities are initiating

practical steps toward establishing platforms that

would support the infusion of robotics into all levels

of Nigeria’s education system. For instance, in October

2017 the United States Diplomatic Mission to Nigeria

partnered with RoboRave International, a United

States of America based robotics academy to train

460 Nigerian students, teachers, and scientists on

hands-on robotics and donated a hundred robots to

the participating school in a bid to inspire robotics

education in Nigeria [10]. Also, it is worth mentioning

that some local entities are not left out of this

eﬀort. The ACI computer education is one of them;

here all they do is build robots. It was established

by Olaoluwa Balogun, an undergraduate student of

the Obafemi Awolowo University (OAU) in the year

2011 as a non-proﬁt organization that trains young

Nigerians on programming and robotics [11]. In the

present paper, we propose our Edu-Rover (abbreviation

for educational rover). This is a robotic unmanned

vehicle for teaching STEM-related practical concepts in

schools.

2. Related Works

To sustain the advancement of robotic technology, there

is an apparent need to introduce robotics into all

levels of the education system [12]. According to [13]

and [14], robots could be used as eﬀective apparatus

for teaching diﬀerent technical concepts in schools;

also [15] suggests that robotics could be applied as

conceptual tools for teaching Mathematics in schools.

The impetuous need to prepare the younger generation

for the coming age of automation, robotics, and

Artiﬁcial Intelligence (A.I.) has prompted educational

policymakers to contemplate the introduction of

robotics into all level of the national educational system

[16]; hence bringing about the need for a new regime

of specialized teachers and teaching instruments. These

have inspired many visionaries, roboticists, educational

technologists, and instrument makers into the research

and development of revolutionary teaching gadgets

that would enhance the eﬀectiveness of robotics

education in schools. For example, [17] proposed a new

methodology for teaching automotive mechatronics

courses in the universities. From their study, they were

able to show that the approach of handing out lecture

materials beforehand and having the student learn by

practicing in the laboratory can increase the interest

and performance of students in STEM subjects rather

than a purely theoretical approach as it is done in

many universities. Also, [18] proposed an approach

to increasing students’ passion for computing and

STEM related education by having them solve the

logical problem in robot programming using the LEGO

Mindstorms kits. According to them, this could enable

students to discover their natural abilities and make the

most appropriate career choice in STEM.

In another study, [19] developed an experimental

platform of a quarter vehicle model to enhance the

teaching-learning system of vehicle dynamics with a

focus on the control of vehicle suspensions’ dynamics.

From their work, it was deduced that students can

have a better understanding of STEM-related concepts

by exploiting the experimental and research-based

learning approach. Similarly, [20] developed a learning

environment for middle and high school students

that uses telerobotics as a mechanism to provide the

students with the ability to remotely manipulate and

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control real robots and their environment through

a Web-based interface to promote education in

Physics, Computer Science and Mathematics at the

middle school, high school and undergraduate levels.

According to them, working with robotics environment

can oﬀer excitement to a wide population through the

Internet, as an Internet of Things (IoT) application.

The above reviews are necessary because they reveal

the importance of adopting the robotic apparatus for

STEM education, which deﬁnes the purpose of our

work. Based on the report of [21], we have identiﬁed

the role of using vehicular models like the teleoperated

drones and wheeled robots to teach STEM concepts.

This is because vehicles are multi-technical systems

which entails the synergy of Physics, Mechanical

designs, electronics, and software applications. There

is a whole lot of insight a student of STEM courses

could gain from studying a vehicular system; little

wonder the children, especially little boys, are very

fascinated when they play with toy cars [22]. The

ingenuity of many renowned automotive designers

and navigational roboticists is traceable to their

childhood experiences with technological transport

toys, through which they learned the rudiments of

Physics, mechanism, and control beforehand [23]. To

enhance this approach to learning, we have developed

the Edu-Rover – an IoT-based robotic vehicle system

for teaching STEM concepts. These include the concept

of machine design, remote control, servomechanism,

and embedded programming as applied to navigational

robotics, for all levels of STEM education.

3. Materials and Methods

The Edu-rover robot is a software-driven system that

comprises of several subsystems that synchronously

work together to achieve the desired motion. The

Figure 1 shows the generic model of the Edu-Rover

system. This consists of a control system and an

internal mechanism. These interact precisely with each

other to drive the system. The Edu-Rover has a man-

computer machine (MCM) interface that involves an

ordinary radio frequency (RF), a wireless-ﬁdelity (Wi-

Fi) connection, or the combination of both. These

ensemble constitutes the system’s control network.

In this network, the RF is used as the media for

information exchange between the human operator and

the vehicle’s internal mechanism through the external

control computer (ECC) within the line-of-sight (LoS),

and also for the wireless relay of video feedbacks from

the onboard video camera (i.e. CAM) to the personal

computer (PC) to enhance visual observation of the

vehicle’s terrain. The Wi-Fi is used to establish an

alternative or higher level medium for teleoperation via

internet connection between the human operator and

the ECC (while it is connected to the vehicle’s internal

Figure 1. Block Diagram of the Edu-Rover System

Figure 2. Model of the Edu-Rover system

mechanism) through a portable device like the Android

system when the human operator is beyond LoS or in

a very remote location. In this manner, the Edu-Rover

system is essentially a cyber-physical system, which

involves the ﬂow of sensory data, control signals, and

visual/video feedback between the human operator and

the vehicle’s internal mechanism over an IoT-integrated

wireless control network.

3.1. Edu-Rover System: Design and Concepts

The Edu-Rover system is a simple rover design, which

is remotely controllable with a desktop computer to

demonstrate the "drive-by-wire" concept. The internal

mechanism of Edu-Rover is made-up of some active

components that include the driving mechanism,

steering mechanism, sensors, and a controller. A control

algorithm was formulated and used to integrate these

components into a functional mechatronic system. The

Figure 2 shows the 2D model of this system.

For navigation, Edu-Rover uses a high-torque drive

system and a servo-mechanical steering system. The

drive systems consist of a speed-reduction geared-

motor that transmits equal power to the duo-rear

wheels. The two rear driving wheels are attached to the

load shaft to convert the rotary motion of the drive-train

into the propelled linear motion of the robot, either

to the forward or reverse direction, as dictated by the

controller. Also, with the cushion eﬀect of the rubber

material used in lining the wheels and its large area in

contact with the ground, enough traction is produced to

propel our robotic vehicle system.

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The steering mechanism of Edu-Rover is a servo-

controlled Ackermann steering system – an improve-

ment on the steering design of [24]. Its design layout

and physical construction is shown in the Figure 3. Edu-

Rover is steered whenever the rotation of the steering

lever converts to the linear motion of the steering

linkage. The servo can position the steering lever in

three orientations on the horizontal plane i.e. 0°, 90°,

and 180°. If the steering lever is oriented at angle 0°,

the steered wheels turn left. At 90°, they align straight,

while at 180° they turn right, according to the Ack-

ermann steering geometry. The servo produces a stall

torque, τ

servo

of 1.0787 Nm at an angular velocity ω

servo

of 6.5440 rad/s at 5V DC supply. The steering radius

(i.e. length of the steering lever), r is 0.045 m.

The tangential force generated by the steering lever is

evaluated as

servo

1.0787Nm

0.045m

= 23.971N, (1)

hence, the power of the steering system is in turn

evaluated as

steering

= τ

servo

× ω

servo

= 7.0590W. (2)

Further details concerning the mechanics of the

Edu-Rover system is discussed in [25]. This analysis

provides a basic understanding of robot locomotion

and the underlying mechanics as a STEM concept. In

eﬀect, this could be applied to the primary and junior

secondary education, within the context of introductory

technology, to prepare young pupils for future career

prospects in the ﬁeld of vehicle design.

Figure 3. Depiction of the steering mechanism

3.2. Electrical Sub-system: Electronics and Sensors

The embedded controller of Edu-Rover is controlled

and instructed using ATmega328P microcontroller.

This is programmed as a semi-automatic controller. It

monitors its serial communication port continuously in

anticipation of radioed control signals from the human

operator through the ECC. This embedded controller

interacts wirelessly with the ECC in a master-and-slave

architecture. Here, the embedded controller functions

as the slave while the ECC functions as the Master.

The peripherals of the embedded controller include the

relay-logic motor controller, the steering servomotor,

and four navigational sensors. The navigational sensors

include an inertial measurement unit (IMU), ultrasonic

sensors, a GPS sensor, and a compass sensor as shown in

Figure 4. The relay-logic motor controller is electrically

interfaced with the embedded controller. It contains

two discrete relays that are wired together to form a

two-channel relay H-bridge as shown in Figure 5. This

can power the driving motor of Edu-Rover in either

clockwise or counter-clockwise direction. The relay-

logic powers the motor to spin clockwise if a logical

HIGH is applied to the pin IN1 and a logical LOW to

pin IN2 and, vice-versa for the driving motor to spin

counter-clockwise. The relay-logic motor controller also

functions as an electromagnetic isolator that protects

the embedded controller which runs on 5 Volts from a

24 Volts source that powers the driving motor.

Figure 4. Navigational sensors of the Edu-Rover System

Figure 5. The Relay-Logic Motor Controller (contains two relays

connected to form H-bridge circuit)

The MG995 Servo is used for the precision control

of the angular position of the steering lever, which in

turn, displaces the steering linkage to and fro, to steer

the vehicle towards the desired direction. To control the

steering system of Edu-Rover, the embedded controller

sends electrical pulses of variable width to the steering

servo, through its control wire, by a process known as

pulse width modulation (PWM). The steering servo can

only be controlled to rotate the steering lever by 90°

in either direction for a total of 180° rotation angle.

The PWM signal sent to the steering servo from the

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embedded controller determines the position of the

steering lever at any instant. Based on the duration

of the pulse sent to the steering servo via its control

wire; the steering lever is rotated to the desired angular

position. The steering servo continuously anticipates a

pulse every 20 millisecond (ms) and the length of the

pulse determines the angular position of the steering

lever. A pulse of 1.5 ms will place the steering lever at

the angular position of 90°. A pulse which is shorter

than 1.5 ms (e.g. 1.0 ms) will rotate the steering lever

in the counter-clockwise direction and place it at the

angular position of 0°; while any pulse which is longer

than 1.5 ms (e.g. 2.0 ms) will rotate the steering lever

in a clockwise direction and place it at the angular

position of 180°. The Figure 6 describes this process.

The vehicle is aligned to drive in a straight line if the

steering lever is placed at the angular position of 90°.

If the steering lever is positioned at 0°, the vehicle is

steered towards the right-hand side and the left-hand

side, if the steering lever is positioned at 180°.

Figure 6. Diﬀerent Pulse Widths and the corresponding Servo

angular positions and steering action(s) of the vehicle

3.3. Software Subsystem: Control Logic and

Algorithms

The software structure of Edu-Rover’s control system

comprises several embedded blocks of algorithms and

logic, which controls its operation – navigation and

perceptual responses. These include blocks of programs

for remote-controlled driving, steering, anti-collision

control, and sensory feedback. These were written

in C++ programming language and compiled onto

the embedded controller. The software structure of

Edu-Rover is described in Figure 7. The algorithms

of this software system are extensively discussed

in Sub-subsection 3.3. This encapsulates conceptual

techniques that could be used to teach object-oriented

programming (OOP), as a STEM subject. Following the

concepts in [26], some important subject-matters that

can be learned from the software system of Edu-Rover

include software organization, bit-wise programming,

physical computing, and microcontroller-based OOP.

Figure 7. Software structure of the Edu-Rover system showing

diﬀerent blocks of embedded algorithms and logic

Tele-autonomous Control Algorithms. This comprises two

blocks of algorithms – the tele-driving and auto-

driving algorithm, for tele-operated and autonomous

control respectively. The former describes a selection

control structure that logically maps the command

of the remote human operator to the target control

function, at any instant of time. In this logic,

the unique American standard code for information

interchange (ASCII) characters are mapped to diﬀerent

preprogrammed motions of the Edu-Rover system.

Here, the microcontroller continually observes its serial

port for incoming signal(s) and compares it to its

conditional constants, in order to execute the block

of program whose conditional constant value matches

that of the incoming signal. For instance, if a block

of programs contains statements for actuating forward

driving, the micro-controller causes Edu-Rover to move

in the forward direction for a given duration of time.

The logic of this function is described in Algorithm 1.

In the absence of serial control signal(s) from the human

operator, the robot automatically switches to the auto-

driving algorithm (i.e. autonomous mode), through the

activation of Algorithm 2, by means of function calls.

Based on the deﬁnitions of [24] and [27], the inter-

switch between Algorithm 1 and Algorithm 2 describes

the implementation of a tele-autonomous system – a

shared control between a human operator and the

computer.

Linear-motion and Steering Algorithm. To perform drive-

by-wire motions in 2D planes, the Edu-Rover software

system incorporates two motion control algorithms.

These are linear-motion algorithm (i.e. Algorithm 3)

and steering algorithm (i.e. Algorithm 4). During the

operation of the Edu-Rover system, Algorithms 3 and

4 responds to function calls (in the form of "go to"

statements) from either Algorithm 1 or 2 to perform

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Algorithm 1 Tele-driving Algorithms

Require: serialPort

1: function teleDriving

2: while serialPort > 0 do  ASCII code is on the

serial port

3: controlSignal ← serialPort

4: if controlSignal = ’F’ then

5: goto forward

6: continue for 1 seconds

7: goto stop

8: else if controlSignal = ’B’ then

9: goto backward

10: continue for 1 seconds

11: goto stop

12: else if controlSignal = ’S’ then

13: goto stop

14: else if controlSignal = ’G’ then

15: goto straight

16: else if controlSignal = ’Q’ then

17: goto left

18: continue for 1.5 seconds

19: goto straight

20: else if controlSignal = ’P’ then

21: goto right

22: continue for 1.5 seconds

23: goto straight

24: end if

25: end while

26: while serialPort ≤ 0 do  No ASCII code on the

serial port

27: call autoDriving

28: end while

29: end function

the electrical and logical operations in Subsection 3.2.

Algorithm 3 describes a switching control structure,

whose basic function is to switch the logical states

of the 2-channel relay as shown in Figure 5 and as

so, rotates the driving motor either in the clockwise

or counter clockwise direction. The syntax of the

embedded software statements for executing linear-

motion control is given in Listing 1. This particular

statements cause the Edu-Rover system to move in the

forward direction. For the reverse motion and brake,

the logical states in Listing 1 are varied according to

Algorithm 3.

Listing 1: Forward-motion Control source codes

/* Object f o r forward dr i vin g * /

forward :

{

d i g it al W r i t e ( relay_1 , HIGH ) ;

d i g i t a l W r i t e ( relay_2 , LOW) ;

t e l e D r i v i n g ( ) ;

}

Algorithm 2 Auto-driving Algorithms

Require: proximitySensor

Require: serialPort

1: function autoDriving

2: while serialPort ≤ 0 do  No ASCII code on the

serial port

3: distance ← proximitySensor

4: if distance ≤ 30cm then

5: goto stop

6: goto backward

7: continue for 1.5 seconds

8: goto stop

9: goto left

10: goto forward

11: continue for 1.5 seconds

12: call autoDriving

13: else if 30cm < distance ≤ 60cm then

14: goto stop

15: goto backward

16: continue for 1 seconds

17: goto stop

18: goto right

19: goto forward

20: continue for 1 seconds

21: call autoDriving

22: else if distance ≥ 90cm then

23: goto forward

24: end if

25: end while

26: while serialP ort > 0 do  ASCII code on the

serial port

27: call teleDriving

28: end while

29: end function

To control the steering system of Edu-Rover, the

branches in Algorithm 4 are consecutively called by

Algorithm 1 or Algorithm 2 to execute the motion

schedule. This involves the variation of the steering

angle according to Figure 6. The syntax of embedded

software statements for executing steering control are

given in Listing 2. This particular statements cause the

Edu-Rover system to steer towards the left. To drive

straight or steer towards the right side, the steering

angle in Listing 2 is varied according to Algorithm 4.

Analogous to the conventional computer system,

the input-processing-output characteristics of the Edu-

Rover software system describes how electrical signals

(i.e. inputs) from the keyboard and sensors are used to

control the motion (i.e. output) of a mechanical system,

through the computer (i.e. processor). Thus, providing

an intuitive understanding of how the computer system

works.

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Listing 2: Steering control source codes

/* Obje ct f o r s t e e r i n g to the l e f t * /

l e f t :

{

s t e e r i n g . w ri te ( 1 8 0 ) ;

t e l e D r i v i n g ( ) ;

}

Algorithm 3 Linear-motion Algorithm

Input: goto ⇒ f orward, backward, stop

Output: Logical_States

Output: call ⇒ teleDriving

1: procedure Relay Switching  Controls drive motor

2: forward:

3: Relay_1 ← 1

4: Relay_2 ← 0

5: call teleDriving.

7: backward:

8: Relay_1 ← 0

9: Relay_2 ← 1

10: call teleDriving.

11:

12: stop:

13: Relay_1 ← 0

14: Relay_2 ← 0

15: call teleDriving

16: end procedure

Algorithm 4 Steering-control Algorithm

Input: goto ⇒ straight, lef t, right

Output: pulseW idth ⇒ steeringAngle

Output: call ⇒ teleDriving

1: procedure Servo Signaling  Turns steering angle

2: straight:

3: SteeringAngle ← 90

◦

4: call teleDriving.

6: left:

7: SteeringAngle ← 180

◦

8: call teleDriving.

10: right:

11: SteeringAngle ← 0

◦

12: call teleDriving.

13: end procedure

3.4. Control Architecture

For the operation of Edu-Rover as an IoT device, we

provided the control model in Figure 8. This allows

it to integrate an internet-enabled ECC for both LoS

and beyond LoS control. The later control channel

involves an internet connection between ECC and

third-party hardware (e.g. an Android device). This

becomes useful whenever the human operator needs to

drive Edu-Rover from a remote location. Thus, we can

reconﬁgure the Edu-Rover system to have two inter-

system communication interfaces. The ﬁrst interface

is the wireless communication between Edu-Rover’s

internal mechanism and the ECC, while the second

one is between the ECC and the human operator

(which alternatively involves the Internet as earlier

mentioned). In this conﬁguration, the ECC only acts as a

gateway between the vehicle’s internal mechanism and

the outside world.

Figure 8. Edu-Rover Control Architecture

4. Results, Application, and Discussion

Using the available materials and technology in the

Nigerian environment, we prototyped Edu-Rover as an

unmanned vehicle system and demonstrated it before

diﬀerent groups of students in several workshops to

ascertain its applicability as an instructional apparatus.

During the demonstration of Edu-Rover, the students

performed test procedures with Edu-Rover. We also

examined their knowledge of its working principles

to ascertain the pedagogical signiﬁcance of Edu-

Rover. The Edu-Rover vehicle was assembled and

demonstrated to the students as shown in Figure

9. We issued questionnaires to two sets of 105

participating students at the completion of their hands-

on exercises to rate on a scale of zero to ten how

Edu-Rover system improved their STEM knowledge.

This questionnaire was restricted to their knowledge of

Physics, Mathematics, and Computing, which underlies

our Edu-Rover system. The bar chart in Figures 10 and

11 are the graphical representations of the results. Also,

a survey was carried out to determine the interest of

participant teachers in the application of Edu-Rover to

their subjects of specialization. The result of this study

is shown in Figure 12.

From the Figures 10 and 11, it is palpable that

a larger proportion of the students preferred the

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(a) The developed system (b) STEM-based teaching (c) Technical demonstration

Figure 9. Live Exhibition of Edu-Rover to the students in a robotics experimentation session

1 2 3

5 6 7 8 9 10

Ratings

Number of Students

Physics

Mathematics

Computer Science

Figure 10. Sample-1: Students Course Assimilation Ratings

using Edu-Rover

1 2 3

5 6 7 8 9 10

Ratings

Number of Students

Physics

Mathematics

Computer Science

Figure 11. Sample-2: Students Course Assimilation Ratings

using Edu-Rover

adoption of Edu-Rover as an instructional apparatus

for STEM education, with Computer Science at the

leading edge. This they say, could help them to visualize

and physically experience the science and engineering

theories they have been learning. The implementation

of this project by each team helped to recall and

enhance their knowledge in the Mathematics of the

system, Physics of the mechanism, and Computer

Science underlying the control algorithms. From Figure

12, it can be deduced that the application of Edu-

Rover for STEM education would have higher impact

on Computer Science and Engineering in relation to

other STEM subjects; which unsurprisingly, are the

two major disciplines upon which future advances

in robotics and automation would apply. Also, some

participant teachers suggested that our Edu-Rover is

useful and applicable for teaching and demonstrating

the rudiments of automotive technology in schools,

which could signiﬁcantly prepare talented pupils for

a future career in the emerging ﬁeld of autonomous

vehicle systems.

5. Conclusion

In this paper, we discussed the need for practice-

oriented STEM education in schools, with a focus on the

observed inadequacy of hands-on learning technology

in Nigerian schools. Based on our current development,

we hereby propose and advocate a step towards

the improvement of STEM education; through the

introduction of hands-on robotics to school curricula.

We implemented an unmanned robot-vehicle prototype

to this eﬀect. This involved the physical implementation

of Edu-Rover and a mock adoption of the system for

teaching STEM concepts. Here, we made use of the

materials that are easily accessible in the Nigerian

environment to show that the schools can actually

start the introduction of robotics education on a low

budget phase. Questionnaire data were collected from

the participating students, to ascertain how the Edu-

Rover inﬂuences their conceptualization of Physics,

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12 2020 - 03 2021 | Volume 8 | Issue 26 | e2

Edu-Rover: Application of Unmanned Vehicle Systems for Robotics and STEM Education in Nigeria

Physics

10%

Mathematics

10.8%

Computer Science

51.6%

Engineering

20%

Art

7.6%

Figure 12. Classiﬁcation of teachers’ interests according to subjects of specialization

Mathematics, and Computer Science subjects. From the

results, we observed that the Edu-Rover system and

the associated didatics excited their enthusiasm in the

application-oriented ﬁeld of robotics, and as such, can

be inculcated into STEM education in schools. Also,

our initiative has motivated the students’ enthusiasm

to delve into the ﬁelds of Computing and Robotics.

We therefore recommend that further research in

this area be focused on the development of robotics

curriculum and standard laboratory robots for teaching

and learning purposes, especially in Nigerian schools.

With this, we could envisage that Nigeria in no time,

would join the league of technologically advanced

countries of the world.

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