Microsoft Word - Autonomous Drone report Assignment.docxAutonomous Drone I built an autonomous...

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Microsoft Word - Autonomous Drone report Assignment.docx
Autonomous Drone

I built an autonomous drone with raspbe
y pi andNavio2. I am going to attach a pdf for the
parts that I used to build the drone. This is a engineering Capstone report so please be VERY
TECHNICAL.

These are the things that need to be written about:

1) Construction of the drone, parts selections, and power calculations, etc.
2) Autonomous flight (I wrote python scripts for autonomous flights, and I can provide that
if needed.)

I ATTACHED ANOTHER CAPSTONE REPORT THAT MIGHT HELP A LOT BECAUSE THAT REPORT
DOES GOES TECHNICAL AND WHEN YOU WRITE THE REPORT, PLEASE REMEMBER YOU HAVE
TO WRITE IT BASED ON MY DRONE AND NOT THE ONE IN THE REPORT EXAMPLE THAT I
PROVIDED.

I have attached few pictures below, just so you can see what the drone looks like.

It must be 12 pages long or 3000 words.

FYDP - Final Report

Faculty    of    Mechanical    and    Mechatronics    Engineering

AUTONOMAPPR
UAV Construction Site Mapping

Final    Report
MTE    482









Group    35

XXXXXXXXXX     Rishab    Sareen
XXXXXXXXXX     Hugo    Louis    Seize
XXXXXXXXXX     Teodor    Mihai    Tiuca
XXXXXXXXXX     Pavel    Shering

Autonomappr
8    Hickory    St.    W
Waterloo,    ON
N2L    3H6

April    2,    2018

Professor    Jan    Huissoon
Department    of    Mechanical    and    Mechatronics    Engineering
University    of    Waterloo 
200    University    Ave.    W 
Waterloo,    ON,    N2L    3G1

Dear    Professor    Huissoon,

Enclosed    is    a    detailed    design    report    covering    all    aspects    of    the    MTE    482    fourth    year    capstone    design
project    titled    Autonomappr.    The    project    is    an    autonomous    drone    developed    to    enable    automation    on
construction    sites.    This    report    covers:

• Final    Design    and    Analysis
• Testing    and    Performance    Results
• Final    Project    Scheduling    and    Budgeting
• Further    recommendations

We    would    like    to    acknowledge    the    work    of:    Hugo    Louis    Seize    –    integration    lead,    Teodor    Mihai    Tiuca
–    software    lead,    Rishab    Sareen    –    hardware    lead,    Pavel    Shering    –    testing    lead,    for    their    contributions
in     designing     this     project     and    writing     this     report.    We    would     also     like     to     acknowledge     Professors
Sanjeev    Bedi,    Steven    Waslander    and    Jan    Paul    Huissoon    for    their    mentorship    during    this    project.

We    are    the    sole    authors    of    this    report    and,    unless    otherwise    stated    and    properly    referenced    in    the
eport,    the    entire    content    of    this    report    is    original    work    done    by    us.    We    have    all    read    the    report    and
are    aware    of    the    content.    The    content    of    this    report    has    not    received    credit    in    this    or    any    other    course
that    we    have    taken    in    the    past    or    are    cu
ently    taking    at    this    time.     

Sincerely,
Group    35

Hugo    Louis    Seize     _____________________________         Rishab    Sareen     _____________________________



Teodor    Mihai    Tiuca         _____________________________     Pavel    Shering         ____________________________
     i
Executive    Summary

This    report    describes    the    implementation    of    the    final    design    presented    in    MTE    481    report.
The    report    outlines    the    final    design,    major    design    changes,    testing    data    and    final    budget    and    schedule
of    the    project.

Motivation    for    the    project    comes    from    the    need    to    drive    automation    in    one    of    the    deadliest    industries
with     approximately    10.1     deaths     per     100,000     employees.    Moreover,     construction     projects     are     on
average     80%     over     budget     and     20    months     behind     schedule.     Due     to     an     ad     hoc     environment     any
autonomous     machinery     on-site     requires     an     up-to-date     site     model     for     navigation.     The     proposed
solution    is    an    autonomous    mapping    drone    that    flies    over    the    site    and    constructs    this    model    by    feeding
image    data    through    a    custom    data    pipeline.

The     system     is    designed     based     on     cost,     time,     speed,     resolution     and     other     constraints     and     criteria
outlined    in    section    1.0.    The    hardware    platform    consists    of    a    Lynxmotion    HQuad500    Base    Kit    drone
frame    with    Raspbe
y    Pi,    a    Navio2    shield    flight    controller    and    a    GoPro    Hero    5    for    imaging.    Custom    3-
D    printed    dampening    mounts    for    the    camera    and    the    computing    unit    are    designed    and    decrease    high
frequency    vi
ations    by    2.5X.    The    final    hardware    platform    costs    $1417.46    and    weighs    1456    grams,
utilizing    about    30%    of    the     total    possible    payload    of     the    drone.     It    achieves    a    max     flight    time    of    12
minutes.

The    Ardupilot    open    source    software    stack     is    used    for    controlling    the     flight    of     the    drone.    Through
control    parameter    tuning    0.135    P    gain    is    selected    for    the    roll/pitch    PID    control    loops    as    it    provided
the    tightest    bound    on    e
or    from    the    control    signal.    Ardupilot    also    enables    flight    autonomy    with    flight
paths    that    are    generated    with    a    custom    script    that    allows    the    user    to    specify    the    location    of    the    site
with    longitude    and    latitude    or    address.

Image    data    is    then    transfe
ed    to    an    AWS    EC2    instance    for    processing,    using    OpenDroneMap,    creating
a    point    cloud.    The    point    cloud    is    then    filtered    with    an    adaptive    filter    and    outliers    are    discarded.    The
filtered    point    cloud    is    then    meshed    into    a    3D    model.    This    model    is    then    uploaded    to    a    server    and    can
e    accessed    through    an    API.    The    model    can    be    enriched    through    a    custom    web    app    designed    using
AngularJS,    ExpressJS    and    WebGL.    Site    managers    can    access    the    orthophoto    of    the    construction    site
and    label    roads    and    points    of    interests,    which    are    then    accessible    via    the    same    API.

Through    testing    of    the    system    on    the    Columbia    Ice    Fields    construction    site,    an    exponential    trend    in
the    overlap    percentage    between    images    and    number    of    points    generated    in    the    point    cloud    is    found.
Additionally,    a    non-linear    relationship    is    found    between    the    computation    time    and    the    number    of
images    processed    through    the    pipeline,    thus    creating    a    trend    between    quality    of    the    model    and    cost
of    computation.

Lastly,    the    project    comes    in    on    time    as    the    platform    and    test    data    were    ready    for    presentation    on
symposium    day.    Additionally,    the    project    is    within    its    constrained    $3000    budget    with    the    total    cost
of    all    components,    including    hardware,    totaling    to    $2827.10.
     ii
Table    of    Contents
1.0 Introduction........................................................................................... XXXXXXXXXX1
1.1 Background ........................................................................................... XXXXXXXXXX1
1.2 Needs Assessment ................................................................................. XXXXXXXXXX2
1.3 Problem Formulation ............................................................................. XXXXXXXXXX3
1.3.1 Project Goal ................................................................................................. XXXXXXXXXX3
1.3.2 Project Objectives ....................................................................................... XXXXXXXXXX3
1.3.3 Constraints ................................................................................................. XXXXXXXXXX3
1.3.4 Criteria ........................................................................................................ XXXXXXXXXX4
1.4 Design Review ....................................................................................... XXXXXXXXXX4
2.0 Final Design Summary .......................................................................... XXXXXXXXXX5
2.1 Drone Hardware .................................................................................... XXXXXXXXXX6
2.1.1 Final Hardware Architecture ..................................................................... XXXXXXXXXX6
2.1.2 Damper Design ........................................................................................... XXXXXXXXXX8
2.1.3 P Gain Control Parameter Tuning (Roll and Pitch) ...........................

autonomous-drone-report-assignment-hy5xaula.pdf drone-report-example-qogm1xzm.pdf quadcopter-parts-for-s550-frame-cmhkhvp1.pdf

Amar Kumar · Accepted Answer

Autonomous Drone with Raspberry Pi and Navio2
Executive Summary
The execution of the final design given in the report is described in this report. The study details the drone's final design, parts selections, and power estimates, among other things. This sort of stages is extremely proper for instructing, since they incorporate an incredible variety of information regions like unbending strong mechanics (minutes and inertial tensors, rotational networks, Euler points), applied science (quaternions), electronic Power (electronic speed regulators), computerization (vehicle control), and so forth. 
Rotating wing airplane with multi-rotors started to plan, and surprisingly fly effectively, at the start of the last century. They were, notwithstanding, right off the bat supplanted by the autogyro, whose principal rotor isn't mechanized and in this way by helicopters given the intrinsic insecurity of numerous rotor structures. In the accompanying figures you can see the first known quadcopter and some airplane with this setup of the mid-twentieth century.
If the stability of cells (aircraft structures) with many rotating wings is substantially more complicated than that of helicopters, one could wonder what benefits they provide and why they are experiencing such a boom. The tail rotor compensates for the reaction torque (Newton's third law) created by the main rotor's movement in a helicopter. The helicopter may also spin across the vertical axis going through the center of the main rotor by adjusting the thrust delivered (yaw movement). The power absorbed by the tail rotor is not used to generate vertical, lateral, or forward thrust under these circumstances. However, it's easy to see how four rotors with opposing rotations that compensate for each other's response pairs will take full use of the power to generate vertical thrust. The efficiency of the multi copter is greater to that of the traditional helicopter in this regard.
 
Table of Contents
Introduction	6
Background	6
Needs Assessment	6
Structure of Quadcopter	6
BLDC Motor	7
Propellers	7
ESC	7
Battery	8
Navio2	8
Raspberry Pi	8
Controller Unit 	8
Software Integration Platform	8
Design of Quadcopter	9
4.0     Power Calculations	10
5.0     Hardware Cost Estimations	11
6.0     Conclusions	12
References	13
3Appendix – A	13
List of Figures
Figure 1 – Quadcopter Design	7
Figure 2 – Architectural workflow of the proposed system	9        
	
List of Tables
Table 1: QUADCOPTER PARTS FOR S550 FRAME						11-12
1.0 Introduction
Robots and quadcopters, among other Automated Aerial Vehicles (UAVs), have revolutionized flying. They assist people in achieving new and great heights. The tactical employment of larger UAVs has grown because of their ability to function in dangerous environments while keeping their human operators at a safe distance. A quadcopter is investigated as a small UAV in this video. It is the automated air vehicles, which are playing an increasingly important role in a variety of areas like as surveillance, military operations, fire detection, traffic signaling, and commercial and current applications. Analysts have been giving close consideration to quadcopters as a result of their intricate attributes. Every one of the examinations start with the quadcopter's essential dynamical model, yet further developed streamlined elements have likewise been added. PID regulators, back-venturing control, nonlinear H control, LQR regulators, and nonlinear regulators with layered immersions are only a couple of the control moves toward that have been examined. Position and disposition readings with a whirligig, an accelerometer, and other estimating gadgets like GPS, sonar, and laser sensors are completely needed for control frameworks. A quadcopter, in some cases known as a quadrotor, is a four-rotor airplane. The rotors are calculated upwards and organized in a square shape with equivalent dispersing from the quadcopter's focal point of mass. The precise speeds of the quadcopter's rotors, which are turned by electric engines, are changed in accordance with control the quadcopter. As a result of its straightforward construction, the quadcopter is a typical plan for little automated ethereal vehicles (UAVs). Quadcopters are utilized in an assortment of utilizations including reconnaissance, search and salvage, building reviews, and the sky is the limit from there.
1.1. Background
A quadcopter is a heavier-than-air aero plane capable of vertical take-off and landing (VTOL) that is propelled by four rotors in a plane parallel to the ground. In contrast to traditional helicopters, a quadcopter's rotors have fixed-contributed sharp edges, and it moves through the air by varying the relative speeds of each propeller. The Omnichen 2, created by Etienne Omnichen in 1920, was the first quadcopter. This specialization completed 1000 successful flights and 360 meters. Quadcopters have made incredible progress in the twenty-first century. Universities, students, and scientists are always attempting to provide more powerful regulator and modelling tools, with the objective of providing point-by-point and precise depictions of real-life quadrotors.
1.2. Needs Assessment
The study's main goal is to improve knowledge about quadcopter design, development, and testing techniques. In the suggested framework, the plan is based on the approximate payload carried by the quadcopter and the weight of individual elements, which results in the determination of electronic parts. Weight, powers following the m, mechanical qualities, and cost are all factors in deciding the materials to use for the design.
2.0. Structure of Quadcopter
The quadcopter's main component is the outline, which has four arms. To accommodate a LIPO battery, four brushless DC motors, a regulator board, four propellers, a camcorder, and numerous sensors, the edge must be light and unbending. The Electronic Speed Regulator controls the speed of BLDC engines. The batteries are placed in the lower half for higher solidity, for example, to have a lower C.G. The engines are positioned on opposite sides, equidistant from the centre. The spacing between engines is usually modified to avoid any streamlined connection between propeller sharp edges.

Microsoft Word - Autonomous Drone report Assignment.docx Autonomous Drone I built an autonomous drone with raspberry pi andNavio2. I am going to attach a pdf for the parts that I used to build the...

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