Master of Mechatronics
scholar.ppu.edu/handle/123456789/46
2024-09-14T01:12:42ZSingle Board Computer ROS-Based Tennis Balls Collecting Mobile Robot
scholar.ppu.edu/handle/123456789/8837
Single Board Computer ROS-Based Tennis Balls Collecting Mobile Robot
Al-Qaisi, Mohammed
With the recent increases of mobile robot deployment that rely on robot operating system (ROS), new
challenges have emerged as a result of the hardware requirements imposed by ROS on the host
computer. Installing ROS on a mobile robot requires the target robot to be equipped with a full
personal computer (PC) with specific specifications. However, deploying ROS on such PC’s will
introduce new issues such as increased size, weight, cost, and power consumption.
This research presents the development and implementation of a fully integrated standalone tennis
balls collecting mobile robot using ROS. The operating system is deployed on a compact, low-cost,
low power consumption, light weight and embedded single board computer (Raspberry Pi 4). The
robot goal is to assist playground attendees by collecting scattered tennis balls. This is accomplished
by integrating and implementing a miniature series of algorithms that construct the robot tasks. These
algorithms are used to detect objects, classify them, plan optimal paths, and avoid obstacles. During
the implementation process, a significant challenge arose in the form of a high computational load on
the main processing unit (CPU). The vision detection algorithm is to blame for this. This was resolved
by using a lighter version of the algorithm, which reduced the computational load.
The proposed method was investigated in this work. The results show that a single board computer
(Raspberry Pi 4) can complete the required objectives and run the algorithms within acceptable
constraints. The vision algorithms performed as expected, detecting all of the objects in the robot
workspace. However, the Raspberry Pi requires a longer execution time than a standard PC to perform
vision tasks. The extra time is due to the Raspberry Pi's hardware resource limitations, as well as the
limitation on utilizing hardware acceleration abilities. Keep in mind that hardware acceleration
employs the graphical processing unit to address vision algorithms in order to shorten execution time.
Furthermore, the A* algorithm was used to help the robot find the shortest obstacle-free path. Other
algorithms are in charge of formulating the wheel's trajectory and control law. All of the robot
algorithms were coded to use fewer computational resources, resulting in less extra execution time.
As a result, the robot is able to complete the tasks in a reasonable amount of time. Finally, the
proposed low-cost solution was shown to be capable of running ROS-based mobile robot algorithms.
CD, no of pages 108, 31166, ميكاترونكس 1/2022
2022-01-01T00:00:00ZDistribution of Functions of Normal Random Variables
scholar.ppu.edu/handle/123456789/5991
Distribution of Functions of Normal Random Variables
Salim, Doaa
The need for the distribution of combination of random variables arises in many areas of
the sciences and engineering. In this thesis, the distributions of two different combination
of Gaussian random variables will be investigated. It is established that such expressions
can be represented in their most general form as the sum of chi-square and the product
of two normal random variables. The distribution of the product of two normal random
variables studied by some authors in the literature in different ways. The first expression
assumed two independent and identical random variables with zero mean and the same
variance. The second one assumed two dependent random variables with zero mean,
same variance, and with a specific correlation coefficient. Closed forms of the probability
density function and cumulative distribution function will be derived, as well as some
statistical properties such as mean, variance, moments, moment generating function,
and order statistics will be studied. All derivation ascertained by using Monte Carlo
simulation. Additionally, method of moment estimation and the maximum likelihood
estimation will be used to estimate the parameter of the derived distribution. Simulation
study carried out using R software. Finally, a practical application well be presented.
mathematics 1/2021 , 31084 , CD , no of pages 93
0002-01-01T00:00:00ZControl of a Ball and Plate System
Using Model-Based Controllers
scholar.ppu.edu/handle/123456789/137
Control of a Ball and Plate System
Using Model-Based Controllers
Al-Haddad, Firas
A ball and plate system (BPS) is a benchmark system in control engineering.
BPS is known to be nonlinear, a multivariable and an unstable system,
has been widely used to investigate and demonstrate new control strategies
that can deal with nonlinearities. The BPS consists of a metal ball, a plate
which can be a resisitive touch screen and two servo motors with a linkage
mechanism to move the plate. A resistive touch screen is placed over
the plate, a plate is pivoted at its center such that the slope of the plate
can be manipulated in two perpendicular directions with two servo motors
to tilte the plate. In this thesis, the modeling of our BPS is based on the
Euler-Lagrange approach, which is represented in the state space form with
plate angles as inputs to the system. Then, the obtained model is linearized
to be able to design linear controllers. Matlab and simulink programs are
used for simulation tests to evaluate the closed loop system response and
to determine the parameters and gains for different controllers. Moreover,
the effect of the disturbances in the measurement is analyzed. Five control
stratigies are selected for static and dynamic position tracking: model
predictive control (MPC), proportional-integral-derivative (PID), state feedback,
linear quadratic regulator (LQR) and linear quadratic tracker (LQT)
controllers. These controllers have been implemented using the Arduino Uno
ATmega328P. Therefore, the aim of this project can be summarized as to
vi
compare between the performance of the five different controllers for balancing
a freely rolling ball in a specific position or to move it in a circle or square
trajectory on the plate with the smallest settling time and the least possible
error achieved for the dynamics of the real-time system.
CD , 31082 , mechatronics 1/2020 , no of pages 113
0012-01-01T00:00:00Zmodelling and experimental investigation of paint mixing process dynamics
scholar.ppu.edu/handle/123456789/5990
modelling and experimental investigation of paint mixing process dynamics
Salman, Majdi
In most paint mixing machines, users usually depend on visual observation
of the paint mixture or they may specify a preset time for stirring chosen
based on previous experience to ensure the homogeneity of the paint, but
this period may be not sufficient to satisfy a perfect homogeneity of the
paint mixture. So, such a practice may lead to inconsistency in paint quality.
In this work, an automatic paint mixing machine that is equipped with
a monitoring and control system has been designed and constructed. This
machine aims to mix and analyze the desired paint color. Arduino Mega
was used as micro-controller and a high-resolution camera was used for paint
image capturing. A mixing algorithm for water-based paints was proposed.
This algorithm guarantees a user to obtain a predefined paint color within a
specific time. That means, the user determines the paint volume and color
as inputs to the algorithm. Then, based on paints commercial database, the
algorithm will specify the needed amount from the three basic colors (red,
green and blue paints) to be mixed.
Experimental investigation of the effects of process parameters of the designed
conventional mixing vessel has been implemented through measuring
the time-varying color state of the paint mixture. The independent variables
include the stirring speed, the tristimulus value of the desired paint color
and the batch volume. The dependent variable is the color distance, which
represents the range between the mixed and the unmixed paint color. The
independent variables are manipulated separately, while reporting the values
of the dependent variable with time. Three empirical models were proposed
including the solution for first, second and complex second order differential
equations. Then, the obtained color distance function was fitted to the empirical
models in order to choose the best fit model, based on minimizing the
objective function using least square method implemented as an algorithm
in the Matlab framework.
The solution for complex second order differential equation provides the best
fit for the observed dynamic curves. It is concluded that the speed of convergence
to steady state increases with increasing stirring speed and decreasing
batch volume. However, changing the tristimulus value of the desired paint
color has no major effect of the speed of convergence to steady state, while
it only changes the steady state distance of the desired paint color. Furthermore,
the developed paint mixing machine can be used for experimental
investigation of kinetic studies of various industrial and environmental reactive
processes.
CD , no of pages 68 , 31080 , master of mechatronics 1/2020
0010-01-01T00:00:00Z