end of semester design report final version
TRANSCRIPT
Autonomous Quadcopter
By:
Jordan Freedner *, Benjamin Kushnir**, James P. Rottinger*, and Daniel T. Worts*
A Senior Project Proposal Submitted in Partial Fulfillment for the Degree of Bachelor of Science in Electrical Engineering* and Bachelor of Science in Mechanical
Engineering**
3 December 2014
* Electrical and Computer Engineering Department, The College of New Jersey, (e-mail:
[email protected], [email protected], [email protected]) ** Mechanical Engineering Department, The College of New Jersey, (e-mail:
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Abstract
An autonomous quadcopter is a multi-rotor helicopter that is capable of navigating
autonomously. It has multiple realistic applications such as last-leg of delivery, land
surveying, crop monitoring, search and rescue assistance, and military usage. The goal of
the TCNJ Autonomous Quadcopter senior project group is to design and construct a
quad-rotor capable of operating on GPS waypoint navigation with multiple flight modes.
It will include a live video feed and multiple layers of hardware and software fail-safe
conditions. Our top-level specifications include a mixed flight time of 15 minutes, a 0.75
mile video transmission radius, as well as object-avoidance sensors (ultrasonic), and a
parachute in case of a total electromechanical failure. The design requires a lightweight
and durable frame with vibration reduction held at utmost importance, in order to
maintain smooth video quality and to avoid interference with the on-board delicate
electronic systems. By the start of the Spring semester, the group plans to have a
quadcopter with fully functional altitude controls (through the use of both a manual
controller and our software), while transmitting a clean video feed.
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Table of Contents
Abstract 2
Nomenclature 5
Introduction 6
Specifications 7
Chapter 1
Background
A: Modern Applications of Quadcopters and Drones 8
B: Commercially Available Quadcopters 9
Chapter 2
Mechanical Design
A: Dynamics and Mechanical Design 11
B: Initial Design Constraints and Considerations 17
C: Arm Design 19
D: Center Plate Design 23
E: Landing Gear Design 27
F: Motor/Propeller Selection and Dynamics 28
G: Vibration Reduction 32
Chapter 3
Power System and Distribution
A: Battery Selection 35
B: Electronic Speed Controls and Voltage Regulator Selection 37
Chapter 4
Communications Systems
A: On Board Data Flow 40
B: Telemetry 41
C: Video 45
D: Manual Controls and Overrides 49
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Chapter 5
Software Control
A: An Introduction to the Role of Software in the Autonomous Quadcopter 50
B: Open-Source Software 51
C: Flight Controller and Sensor Performance 52
D: PID Software Implementation 55
E: Current Status of the Software 59
Chapter 6
Conclusion 60
List of References 61
Appendices
A1: About 62
A2: Realistic Constraints and Engineering Standards 64
B1: Gantt Chart 67
B2: Meeting Minutes 68
B3: Safety Form 70
B4: Materials List 71
B5: Budget 74
C: Quadcopter dynamics state variables 75
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Nomenclature
ADC Analog to Digital Converter
AUW All Up Weight
DAC Digital to Analog Converter
ESC Electronic Speed Control
FCC Federal Communication Commission
GPIO General Purpose Input Output
GPS Global Positioning System
GUI Graphical User Interface
IMU Inertial Measurement Unit
I2C Inter-Integrated Circuit (multi-master, multi-slave, serial bus)
MAVLink Micro Air Vehicle Link
PWM Pulse Width Modulation
RS232 Serial Communication Standard
UAV Unmanned Aerial Vehicle
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Introduction
A quadcopter is defined as a multicopter propelled by four rotors attached to arms
that extend from a central console. Unlike standard helicopters, these multirotors use
two sets of fixed pitch propellers that control the motion of the vehicle through changes
in RPM. The vehicle is capable of hovering as well as rotating about any of the three
reference axes, depending on the thrust being applied from each motor. The stable yet
responsive nature of a quadcopter’s manner of flight is what makes these multirotors so
desirable in small-scale applications. Since they are relatively cheap, simplistic in design,
and maneuverable, there has been a recent push towards their employment in both
militaristic and commercial applications. Quadcopters can be used for search and rescue
mission assistance, structure inspection, land surveying, delivery services, and aerial
support for large events and law enforcement.
As the advantages of implementing unmanned aerial vehicles into society continue
to expand, the research and technology involved in their development is growing rapidly.
With this growth, autonomous flight is becoming more accurate and popular. This
characteristic of new age UAV’s eliminates the need for an operator to be responsible for
the vehicle’s flight and further increases the potential applications for quadcopter usage.
Although there is much debate about the ethical dilemmas regarding drone use, including
issues of privacy and morality, it is obvious that this technology is monumentally
significant, allowing humans to obtain information about and even deliver assistance to
areas that are unsafe or inaccessible.
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Specifications
In order to engineer our quadcopter properly, we first needed to set a series of
specifications and goals that needed to be met. Therefore, we needed to decide what
aspects of the project were vital for project success and define our specific requirements
for them as such. You can see our chosen specifications in the table (3.1) below. We chose
these specifications for a number of reasons. Video and Communications range is
important because we can only safely operate the quadcopter if we can communicate with
it. Therefore, we needed to make our range goal for these project aspects as large as
realistically possible. We determined that even if we lose video transmission, we can still
send failsafe operations to the quadcopter if telemetry communications are still active,
which explains why our telemetry range is larger than our video transmission range.
Flight time is valued in this project because the duration of time the quadcopter can spend
in the air determines how much can actually be done with the quadcopter. This project
would be useless if it were only able to sustain flight for 5 minutes. We chose a 15 minute
flight time goal based off of commercial equivalents and because it allows for full travel
inside of communications range multiple times.
Autonomous Quadcopter General Specifications
Specification Requirement Goal
Quadcopter Mixed Flight Time 12 Minutes 15 Minutes
Telemetry Comm. Range 1 Mile 1.5 Miles
Video Feed Range .75 Miles 1 Mile
Table 3.1: General Specifications
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Chapter 1: Background
Section A: Modern Applications of Quadcopters and Drones
Before going into some of the modern applications of drones, quadcopters, and other
multi-rotor vehicles, it is important to draw a distinction between them and to properly
classify the vehicle described and discussed in this report. First of all, “drone” is a word
commonly used in association with an unmanned aircraft. This is a high-level
classification because it could refer to a vehicle that is piloted on its own given a set of
inputs, or to one that is controlled directly from a remote location. The former type will
be known as “autonomous” throughout this report and the latter is simply a remote-
controlled vehicle. In terms of being a multi-rotor copter, the prefix of the copter simply
refers to the number of arms and rotors on the vehicle; a quadcopter would have four, an
octocopter eight, etc. All that being said, the title of this report is “Autonomous
Quadcopter”, meaning that the vehicle being designed consists of four arms and rotors,
positioned in an X-formation, and is capable of being piloted on its own given a set of GPS
coordinates.
The most commonly-known use of drones, and the most controversial, is their use in
combat operations to perform unmanned bombing missions. Drones designed for this
specific application are known as Unmanned Combat Air Vehicles (UCAVs) and have
been in use for over 20 years but have just recently risen to higher popularity as
technology has allowed for the refinement and sophistication of these vehicles. Beyond
combat, however, it is also widely known that Amazon is working on applying drones to
package-delivery applications to fulfill orders to their customers.
When initially designing this quadcopter, a variety of applications were considered,
some of which are only theoretical at this point, meaning that they have only been
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hypothesized and not implemented to date (as far as is known). The first application that
was considered is using the vehicle to perform 3D-modelling and mapping. This can
theoretically be done through stitching together a large number of images or 3D distance
vectors to a be point where a 3D map of a location can be generated. For the scope of this
project, however, a more general application was selected, and that is to perform land
surveying given a set of GPS coordinates to survey. This type of surveying can be applied
to search and rescue missions, wildlife preservation, and agricultural uses. To accomplish
this, the vehicle will be capable of piloting itself through a set of provided GPS coordinates
and relaying back a video feed from a camera mounted to the bottom of it.
Section B: Commercially Available Quadcopters
When designing any custom-made product, the commercial availability of the product
needs to be considered before committing resources to the project to determine if is
cheaper in the long-term to simply purchase it from a third-party. In the specific
application of this quadcopter, the relevant specifics are autonomous flight, GPS
navigation, flight-time, and transmission distance. The specifications section of this
report states that the specifications for this vehicle include a 15-minute flight time, a
telemetry communication distance of 1.5 miles, on-board GPS, and autonomous flight.
Table 1.1 compares these specifications to those of commercially available pre-assembled
multi-rotor vehicles.
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Vehicle Price Flight Time (min)
Transmission Distance (mi)
GPS Equipped?
Autonomous / Manual
Current Design $1750 14-15 1.5 Yes Autonomous
ProHeli XPX Heavy-Lift Quadcopter
$3757 14-15 1.0 Yes Manual
Parrot AR.Drone 2.0 Elite (No Camera)
$299 < 10 Unknown No Manual
3RD IRIS+ $1729 16-22 1.0 No Manual
DJ Phantom II Vision+
$1399 25 0.5 Yes Hybrid
Table 1.1 - Comparison of the quadcopter to commercially available multirotors
Through researching the multirotors, it was found that many of the companies advertise
a low price for the base model, however, once the additional options were added to
accomplish the desired application, that the price quickly rose. In addition, none of the
commercially available are equipped to be operated autonomously, meaning that
additional time and money would have to be invested in adding that specific feature. Only
the DJ Phantom II is able to navigate through a set of GPS coordinates, however, a remote
control link is still required. The biggest difference between the quadcopter being
designed and the DJ Phantom II is the range. It has been reported that the Phantom loses
serial connection around 200m and will then automatically return to the home point. The
specifications for this quadcopter call for a range of 1.5 miles which provides a much larger
survey range. In summary, if the specifications of this quadcopter are realized, then it can
safely be said that it will be cheaper and more full-featured than anything that can
currently be purchased and used out of the box.
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Chapter 2: Dynamics and Mechanical Design
Section A: Quadcopter Dynamics
Before frame design can begin, an understanding of general dynamics regarding
quadcopter flight must be established. A set of equations can be applied to identify the
dynamic model that guides the motion of a quadcopter, and is available below in a
simplified form (a detailed derivation is provided in the flight dynamics reference).
In order to start an analytical derivation of the equations of motion, rotational
matrices must be created that will help describe the orientation of the vehicle and the
transformation between various frames of reference. Given two coordinate frames as
shown in Figure 2.1, it is necessary to define a rotational matrix that provides a method
of conversion between the two.
Figure 2.1: 2D rotation to create vector p
The vector p can be defined in both coordinate frames; the 𝐹0 frame expresses the vector as:
𝒑 = 𝑝𝑥0𝑖̂0 + 𝑝𝑦
0𝑗̂0 + 𝑝𝑧0�̂�0
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The vector p is defined in the 𝐹1 frame as:
𝒑 = 𝑝𝑥1𝑖̂1 + 𝑝𝑦
1𝑗̂1 + 𝑝𝑧1�̂�1.
By equating these expressions, simple trigonometric properties and matrix
manipulations offer a relationship between the two vectors, as given by:
𝒑1 = 𝑅01𝒑0
Where the rotation matrix, 𝑅01 , from coordinate frame 𝐹0 to frame 𝐹1 for rotation about
the z-axis is defined as :
𝑅01
𝑧−𝑎𝑥𝑖𝑠≜ (
cos (𝜃) sin (𝜃) 0−sin (𝜃) cos (𝜃) 0
0 0 1
).
Right-handed rotation matrices about the y-axis and x-axis are also pertinent and are
found in a similar manner:
𝑅01
𝑦−𝑎𝑥𝑖𝑠≜ (
cos (𝜃) 0 −sin (𝜃)0 1 0
sin (𝜃) 0 cos (𝜃)) 𝑅0
1𝑥−𝑎𝑥𝑖𝑠
≜ (
1 0 00 cos (𝜃) sin (𝜃)0 −sin (𝜃) cos (𝜃)
).
With the rotational matrices determined, various coordinate frames must be
established in order to begin modeling the dynamics of the quadcopter. The most basic of
the systems is the inertial frame 𝐹𝑖, defined as a fixed coordinate frame that remains
stationary with the movement of the vehicle. The vehicle frame 𝐹𝑣 has its origin at the
center of gravity of the quadcopter, but the frame’s axes are aligned with those of the
inertial frame 𝐹𝑖 at all times. The vehicle-1 frame 𝐹𝑣1 is also located at the center of
gravity, but is rotated about unit vector �̂�𝑣 by the yaw angle 𝛹. The subsequent vehicle-2
frame 𝐹𝑣2 is created by rotating the vehicle-1 frame about the unit vector 𝑗̂ 𝑣1 by the pitch
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angle 𝜃. Finally, the body frame 𝐹𝑏 is generated by rotating the vehicle-2 frame about the
𝑖̂𝑣2 axis by the roll angle 𝜙, and is entirely identical to the physical orientation of the
vehicle. Rotation matrices identical to those discussed in regards to vector p can be
applied to relate each successive frame and are summarized in Table 2.1 below.
Frame Transfer Transformation
Equation
Rotational Matrix
Vehicle to Vehicle-1 𝒑𝑣1 = 𝑅𝑣𝑣1(𝛹)𝒑𝑣
𝑅𝑣𝑣1(𝛹) = (
cos(𝜃) sin(𝜃) 0− sin(𝜃) cos(𝜃) 0
0 0 1
)
Vehicle-1 to Vehicle-2 𝒑𝑣2 = 𝑅𝑣1𝑣2(𝜃)𝒑𝑣1
𝑅𝑣1𝑣2(𝜃) = (
cos (𝜃) 0 −sin (𝜃)0 1 0
sin (𝜃) 0 cos (𝜃))
Vehicle-2 to Body 𝒑𝑏 = 𝑅𝑣2𝑏 (𝜙)𝒑𝑣2
𝑅𝑣2𝑏 (𝜙) = (
1 0 00 cos (𝜃) sin (𝜃)0 −sin (𝜃) cos (𝜃)
)
Table 2.1: Rotational Matrix Equations for Frame Transformations
Therefore, the full transformation matrix from vehicle to body frame is simply the
product of each individual rotation matrix, as represented by:
𝑅𝑣𝑏(𝜙, 𝜃, 𝛹) = 𝑅𝑣2
𝑏 (𝜙) × 𝑅𝑣1𝑣2(𝜃) × 𝑅𝑣
𝑣1(𝛹).
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By substituting the matrices provided in Table 2.1 and completing the calculation, the
transformation matrix is shown to be:
𝑅𝑣𝑏(𝜙, 𝜃, 𝛹) = [
𝑐(𝜃)𝑐(𝛹) 𝑐(𝜃)𝑠(𝛹) −𝑠(𝜃)
𝑠(𝜙)𝑠(𝜃)𝑐(𝛹) − 𝑐(𝜙)𝑠(𝛹) 𝑠(𝜙)𝑠(𝜃)𝑠(𝛹) + 𝑐(𝜙)𝑐(𝛹) 𝑠(𝜙)𝑐(𝜃)
𝑐(𝜙)𝑠(𝜃)𝑐(𝛹) + 𝑠(𝜙)𝑠(𝛹) 𝑐(𝜙)𝑠(𝜃)𝑠(𝛹) − 𝑠(𝜙)𝑐(𝛹) 𝑐(𝜙)𝑐(𝜃)].
To continue the analysis of quadcopter kinematics, it is important to define all
necessary state variables in relation to the various frames formed in the previous section.
Table C.1 in Appendix C provides a set of variables with definitions. The relationship
between position and velocity for this set of variables requires the rotation matrix that
transforms the body frame into the vehicle frame (which calls for the transpose of the
previously defined matrix), and is given by:
𝑑
𝑑𝑡(
𝑝𝑛
𝑝𝑒
ℎ) = (
𝑝�̇�
𝑝�̇�
ℎ̇
) = 𝑅𝑏𝑣 (
𝑢𝑣𝑤
) = (𝑅𝑣𝑏)𝑇 (
𝑢𝑣𝑤
)
= [
𝑐(𝜃)𝑐(𝛹) 𝑠(𝜙)𝑠(𝜃)𝑐(𝛹) − 𝑐(𝜙)𝑠(𝛹) 𝑐(𝜙)𝑠(𝜃)𝑐(𝛹) + 𝑠(𝜙)𝑠(𝛹)
𝑐(𝜃)𝑠(𝛹) 𝑠(𝜙)𝑠(𝜃)𝑠(𝛹) + 𝑐(𝜙)𝑐(𝛹) 𝑐(𝜙)𝑠(𝜃)𝑠(𝛹) − 𝑠(𝜙)𝑐(𝛹)𝑠(𝜃) −𝑠(𝜙)𝑐(𝜃) −𝑐(𝜙)𝑐(𝜃)
] (𝑢𝑣𝑤
)
Where ℎ̇ is defined as the velocity vector along �̂�𝑖 resulting in a sign change in the third
row. This system represents a connection between the velocities in the inertial frame and
the velocities in the body frame, which is necessary for conversion between sensor
readings and observations with reference to the user’s position.
An additional set of equations that helps identify the dynamics of the vehicle is the
solution for the rate of change in roll, pitch and yaw angles defined in the 𝐹𝑣2, 𝐹𝑣1, and 𝐹𝑣
frames, respectively, as functions of the roll, pitch and yaw rates defined in the body frame
𝐹𝑏. Again, this relation can be found using rotational matrix manipulation:
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(𝑝𝑞𝑟
) = 𝑅𝑣2𝑏 (�̇�) (
�̇�00
) + 𝑅𝑣2𝑏 (𝜙)𝑅𝑣1
𝑣2(�̇�) (0�̇�0
) + 𝑅𝑣2𝑏 (𝜙)𝑅𝑣1
𝑣2(𝜃)𝑅𝑣𝑣1(�̇�) (
00�̇�
)
Where each additional angular rate requires a subsequent rotation applied to it. Assuming
that �̇�, 𝜃,̇ and �̇� are relatively small, the rotational matrices of these rates can all be
equated to the identity matrix by using the matrices tabulated in Table2.1. Applying the
identity and rotation matrices and inverting, the rates of the absolute angles of the body
frame are found to be
𝑑
𝑑𝑡(
𝜙𝜃𝛹
) = (�̇�
�̇��̇�
) = (
1 sin(𝜙)tan (𝜃) cos(𝜙)tan (𝜃)0 cos (𝜙) −sin (𝜙)
0 sin(𝜙)sec (𝜃) cos(𝜙)sec (𝜃)) (
𝑝𝑞𝑟
).
A quadcopter maintains stability using counteracting torques provided by two
pairs of motors spinning in opposite directions (with each pair located along an axis of
rotation). A visualization of the forces, torques, and angles caused by each motor is
provided below in Figure 2.2 (where the subscripts f, r, b, and l identify the front, right,
back, and left of the vehicle).
Figure 2.2: Forces, torques, and angular movement of quadcopter frame
The net force is simply the sum of each motor’s applied force, given by:
𝐹 = 𝐹𝑓 + 𝐹𝑟 + 𝐹𝑏 + 𝐹𝑙.
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The rolling torque (produced by the left and right motors) is defined as:
𝜏𝜙 = 𝑙(𝐹𝑙 − 𝐹𝑟)
And the pitching torque (produced by the front and back motors) is defined as:
𝜏𝜃 = 𝑙(𝐹𝑓 − 𝐹𝑏)
Where l is given by the perpendicular distance between the center of gravity of the
quadcopter and the axis of rotation of each motor. The yawing torque is affected by the
drag caused by each propeller, and can be quantified by subtracting the sum of the
counterclockwise torques from the sum of the clockwise torques, or
𝜏𝛹 = 𝜏𝑟 + 𝜏𝑙 − 𝜏𝑓 − 𝜏𝑏.
The final force that must be considered in the analysis of the dynamics of
movement is the force on the center of mass due to gravity, given by
𝒇𝑔𝒗 = (
00
𝑚𝑔).
The equation above is applied to the vehicle frame and must be transformed to the body
frame to become relevant in the analysis of the vehicle’s movement. This transformation
is made possible through the derived rotation matrix relating vehicle and body frames,
giving:
𝒇𝑔𝑏 = 𝑅𝑣
𝑏 (00
𝑚𝑔) = (
−𝑚𝑔sin (𝜃)
𝑚𝑔 cos(𝜃) sin (𝜙)
𝑚𝑔 cos(𝜃) sin(𝜙)).
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Upon analyzing this matrix equation, it is important to note that the forces of gravity are
unaffected by the yaw angle. This conclusion is logical because the angle between the
direction of gravity and the x-y plane of the body frame remains unchanged over the entire
range of yaw.
The dynamics of quadcopter flight is an important concept that affects both the
design and testing of the vehicle. Knowledge of the influences that contribute to the
angular and linear movement of the quadcopter can offer substantial guidance in
determining how the motor commands must change to accommodate the observations of
initial testing. This knowledge will facilitate the transfer from visual observation to coding
adjustment requirements and will therefore improve the likelihood of a successful, stable
flight.
Section B: Initial Design Constraints and Considerations
A fundamental component for a stable, reliable quadcopter flight is a rigid and
optimized frame design. The approach to this design begins with the determination of
dimensional requirements for the sizing of the body, specifically the motor-to-motor
distance (the distance between two motor axes measured along the length of the arms).
Selection of this parameter is reliant on two major design constraints. Firstly, the
acceptable minimum spacing between GPS and video transmission devices to avoid
interference is 1ft, meaning that the arm length must agree with this size limitation.
Secondly, the path of the propeller blade must not interfere with the placement of the
controller and parachute in the center. This second parameter is slightly more
complicated to analyze; an iterative process detailed in Section E is used to provide thrust
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calculations for various propellers and motors in order to determine the optimal
combination.
After multiple iterations, a motor-to-motor distance of 21.25” is selected. Both X
and plus configurations are considered for the design (an X-oriented quadcopter will
contain 2 rotors at 45° angles in front of the vehicle when travelling forward while a plus-
oriented quadcopter will have a single rotor directly in line with forward motion). In
general, an X-shaped build offers greater stability while a plus-shaped build provides
increased flight response. This assertion is intuitive; a quadcopter oriented as an X will
generate roll and pitch from a pair of motors on each side, whereas the alternative relies
on a single motor to rotate about a given axis. Since the scope of the project is geared
towards first person video rather than speed and aerobatics, an X-configuration is
selected. This design will provide a more stable video feed and will avoid any interference
caused by a swinging propeller located in the direction of the camera’s frame of capture.
Figure 2.3 below shows a labeled 3D representation of the full quadcopter model:
Figure 2.3: Labeled Front View of Quadcopter SolidWorks Assembly
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The three main structural components of the design are the center plates, the arms,
and the landing gear. Each component is analyzed individually for stress and deflection
characteristics. Although the frame is designed to sustain as much loading as possible, it
is unreasonable to assume that failure will not occur under free-fall crash conditions; the
amount of material needed to withstand such a fall would amplify the weight and price of
the vehicle, and would result in a design that is out of the scope of the project. Therefore,
the rigidity of all mechanical systems are analyzed subject to standard flight conditions
and are designed with factors of safety that are sufficient enough to minimize any
structural damage that should occur from operational malfunction caused by a free-fall
crash of 1m.
Section C: Arm Design
Some constraints that influence the arm design include the placement of various
electrical components (including video transmitter, GPS unit, antenna, and ESC’s) that
are to be mounted along the length of each arm, the required separation given by the
motor-to-motor distance, and the need for minimum deflection under maximum thrust
conditions to ensure that the resultant thrust be entirely perpendicular to the reference
plane of the body. With these constraints in mind, the arms are designed with 9” long
square ¾” 6061-T6 aluminum tubing. Aluminum is chosen over carbon fiber and wood
for multiple reasons. The material offers a high strength-to-weight ratio, is machinable
and accessible, and is entirely cost efficient. Carbon fiber, while exhibiting better strength
characteristics, is difficult to machine and is out of the price range. Wooden arm selection
offers a very lightweight and cheap alternative, but is much more prone to failure than
aluminum. Since rigidity and durability are of utmost importance in the frame design, it
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is more logical to select a stronger, heavier arm material than to design solely for weight
reduction and result in a design that requires constant maintenance and repair. Since
weight is still a significant factor, the sides of each arm are trussed to reduce their weight
without compromising the strength or bending characteristics under typical flight
conditions.
An original consideration for the arm design involved welding 2 long arms in an x-
formation rather than bolting together 4 arms between 2 center plates. This design would
improve the rigidity of the frame and would allow for some material to be removed from
the center plate, thereby reducing the weight and improving the flight time. While
beneficial in theory, maintenance and repairability are factors that cannot be ignored,
especially with components that are under constant loading. With a welded frame, the
slightest issue that arises in any of the arms will require the entire frame to be
disassembled and the arm chassis to be removed and completely rebuilt. Considering the
downsides of this method of assembly, it is decided that welding should be avoided at all
costs.
Stress and deflection analyses are conducted for loading characteristics based on a
maximum thrust production of 1360g from a single motor. The deflection plot in Figure
2.4 (next page) shows a maximum deflection of .06925mm with a factor of safety of 19;
such a small deflection is considered negligible and should not affect operation.
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Figure 2.4: Deflection plot of arm under maximum thrust loading conditions
Additionally, the arms are analyzed under free-fall crash conditions from a 1m drop. The
result of the 300N simulated loading (Figure 2.5) is a factor of safety of 2.28, meaning
failure will not occur even if the quadcopter were to malfunction mid-flight and land
directly on an arm.
Figure 2.5: Von Mises stress plot of arm under 1m freefall crash loading conditions
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The selected motor has a bolt hole spacing that exceeds the width of the aluminum
arm, meaning that a motor mount must be installed. This component is made from 1/8”
aluminum plate and includes holes that correspond with the bolt pattern on the motors
as well as material removed for weight reduction and heat dissipation. Similar to the other
rigid components of the assembly, it is important that the deflection demonstrated by
these mounts under expected loading conditions be minimized. Since the placement of
the motor mount represents an overhang beam, a thicker piece of aluminum is chosen in
order to reduce the effects of the bending moment caused by the applied thrust, which is
assumed to be in line with the axis of the motor. At maximum throttle, the expected
deflection of the component’s outermost edge is insignificant at a value of 0.04266mm,
as presented below in Figure 2.6.
Figure 2.6: Deflection plot of motor mount under maximum thrust loading conditions
An analysis of the stress concentration plot (Figure 2.7, next page) shows that a
significant amount of stress exists at the tip of the bolt hole nearest to the motor. Although
the factor of safety is an acceptable value of 4.89, it is also worthy to note that the area
where stress is maximized is located directly above the square aluminum arm. The extra
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material below this segment will reinforce the motor mount and will distribute the stress
to a section further along the length of the mount where the aluminum arm is not present.
This section is designed with a large fillet to alleviate the critical stresses seen by this part.
Figure 2.7: Von Mises stress plot of motor mount under maximum thrust conditions
Section D: Center Plate Design
The center plate is responsible for attaching all 4 arms together, with the upper
plate holding the controller mount and Tx/Rx antenna in place and the lower plate
holstering the battery and camera mount. Both the upper and lower center plate are
subject to high bending moments, since the weight of the entire vehicle is being
transmitted from the landing gear through the arms into the central console. Therefore,
material selection is as always a key factor in the design: the center plate material
properties should include resilience to bending and impact loads, machinability and
compatibility with the aluminum arms, and aesthetics. Plywood, acrylic, and
polycarbonate are all reasonable material selections for the application. Aluminum is
immediately ruled out due to interference issues with the electronics and wiring and
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carbon fiber is avoided for the same reasons it is not selected as the arm material.
Although plywood offers a cheap and replaceable center plate, it is not aesthetically
pleasing, and does not exhibit sufficient strength characteristics, as it is prone to cracking
along the grain from fatigue stresses. Acrylic sheet offers poor impact resistance, a quality
that is a necessity for a proper center plate design. While slightly more expensive, 3/16”
high-impact polycarbonate sheet is selected for the center plate material due to its high
strength characteristics and resistance to impact loading. The plate is shaped such that
the weight is minimized, bolt placement is optimal for the expected levels of stress, and
the wires are able to be routed comfortably throughout the frame to connect all integrated
electronics.
Like the arms, the center plate is analyzed using maximum thrust loading as well
as free-fall crash conditions. Figure 2.8 and 2.7 (next page) depict the deformation plots
and Von-Mises stress, respectively, for a maximum thrust of 1360g being applied from
each motor. Given this applied loading, the deformation can be considered negligible at a
value of 0.2438 mm and the factor of safety is well within the acceptable limit.
Figure 2.8: Deformation plot of center plate under maximum thrust loading conditions
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Figure 2.9: Von Mises stress plot of center plate under maximum thrust conditions
Stress and deformation plots are shown in Figure 2.10 and 2.11(next page) for loading due
to a crash landing scenario. Under a 500N load, the deformation is significant at 8.126mm
but the plate does not fail due to the high-impact characteristics of the material. The
factory of safety for this loading scenario is 1.88. With the smallest factor of safety in the
design, this component will be the first to fail. These plates are designed with this
consideration in mind, as they are cheap and readily replaceable
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Figure 2.10: Deformation plot of center plate under 1m freefall crash conditions
Figure 2.11: Von Mises stress plot of center plate under 1m freefall crash conditions
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Section E: Landing Gear Design
The landing gear design consists of 4 sets of 2 concentric polyvinyl chloride (PVC)
tubes. The smaller tube is attached to the lower surface of the arm by a compression spring
which will serve to absorb the shock of a crash landing. Not only will this design reduce
the impact force of landing on the arms, but will also allow for the quadcopter to land on
uneven ground without the risk of toppling. The spring is selected based on the expected
loading of a 1m fall in order to ensure that the camera gimbal is at least 2in above the
ground at maximum compression. Calculations show that a steady, balanced landing will
only compress the spring 0.136in: this small displacement is desirable because the
purpose for this spring-damper assembly is to reduce impact caused only by a heavy
landing. When subject to forces exerted from a 1m free fall, the compression of the spring
is 1.39in. Since this scenario is considered worst case, compression is impeded at 2in to
avoid the need for unnecessary material and to leave adequate clearance for the camera
gimbal. A modeled view of a single landing gear assembly is available below in Figure 2.12.
Figure 2.12: 3D model of spring-loaded PVC landing gear assembly
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PVC was chosen over aluminum for this application because it is characterized by
high compression strength while still remaining extremely lightweight compared to the
alternative. The location of the landing gear is limited by the viewing angle of the camera
(to avoid video obstruction), but must be placed such that the moment arm of the load
applied during landing is minimized; a length of 5.5 inches from the central axis satisfies
both of these conditions.
Section F: Motor/ Propeller Selection and Dynamics
Motor and propeller selection is a vital design requirement to ensure stable and
efficient flight of a multirotor. This process can be simplified by analyzing readily
available motor and propeller combinations, computing the thrust requirements needed
to lift the all-up-weight(AUW) of the vehicle, and comparing the characteristics of each
combination. Specifically, it is pertinent to take thrust production, power consumption,
RPM, efficiency, weight, and cost into consideration. Thrust production is the guiding
factor in this selection process, since it is this value that counteracts the weight and allows
the quadcopter to maneuver. A rule of thumb that is used as a standard for quadcopter
design is that the combined thrust of all four motors must generate double the AUW,
meaning that hovering conditions should be achieved at 50% of maximum throttle. This
standard is quite intuitive: hovering at less than this value will cause the vehicle to become
too responsive to changes in throttle, which will reduce stability and increase vibration.
At a higher value, the motors will consume more power than needed to create the
necessary thrust, causing greatly reduced flight time and making the vehicle sluggish and
unresponsive.
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Another consideration in the selection of motors and propellers is the RPM value.
It is optimal to keep the angular velocity of the blades as low as possible; reducing the
RPM will reduce the vibrations commonly caused by electric motors, a necessity for first-
person video applications. As a consequence of reducing the kv rating of the motor (a
constant value that is used to classify motors and is defined by the RPM value with 1V
being applied and no loading), the propeller diameter must increase to produce the same
amount of air flow through the sweep area of the blades. A spreadsheet, shown on the top
of the next page in Table 2.2, is used to organize the motor characteristics calculated using
a maximum blade diameter of 12” and a pitch of 4.5”; although smaller propellers with
larger pitches are also analyzed, they are excluded early in the selection process due to an
inability to meet hover requirements and a significantly reduced efficiency and estimated
flight time.
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Table 2.2: Detailed quadcopter motor spreadsheet
After several iterations of calculations, along with the support of reliable software
used for quadcopter power systems analysis, a Tiger Motor 3508-16 700kv motor with
12" diameter propellers is chosen as the optimal solution. This combination provides
1360g of thrust per motor (manufacturer specification) with hover occurring at 47%
throttle and a 15 minute mixed-flight time in junction with the selected battery. The
specific thrust of a motor is a value closely related to the efficiency, representing the
measure of thrust production, in grams, per unit of electrical power supplied, in Watts.
The selection process is highly dependent on this quantity; with a value of 6.94 g/W the
MN3508-16 is nearly unbeatable and is well worth the price. The specific thrust can be
easily measured through experimental means, and will be scrutinized for conformity to
the manufacturer’s specifications when the testing phase of the project begins. All other
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competitors with similar performance characteristics are either unavailable or do not
meet minimum thrust requirements.
Due to the vehicle’s autonomous functionality, calculations must be carried out to
verify that the sensors responsible for object avoidance have an adequate response time
with respect to the movement of the quadcopter. These calculations are imperative to the
safety of the frame and propellers; if the reaction time is over the range that will allow all
necessary signals to be processed and transmitted to thrust commands within a certain
distance (given by the specifications of the sensors), the quadcopter will not be able to
avoid a crash. Computations for flight dynamics are conducted for a maximum angle of
attack of 45°. For horizontal travel, each motor must operate at 70% throttle, giving a
resultant velocity of 12.33 mph. The time required to traverse the allowable radius of
0.75mi at constant horizontal velocity is 3 minutes and 36 seconds, which verifies that a
round trip at these conditions is achievable given the expected battery life of 15 minutes.
At full throttle, the vehicle moves horizontally at 16.44mph, with a resultant velocity of
23.25mph. These calculations are compared with output of the software used to conduct
motor selection, which estimates a maximum velocity 26.1mph. Some variation with these
calculations exists due to necessary approximations for the drag coefficient and the acting
surface area, but are considered negligible in relation to the time constant characteristics
detailed in Chapter 5.
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Section G: Vibration Reduction
Vibration is a common issue encountered in quadcopter design and must be
accounted for to reduce electronic malfunctions and stabilize video feed. The multiple
possibilities for vibration dampening apparatuses and supplements must be investigated
based on their purpose, functionality, and practicality. Vibration originates from the
motor, travels through the mount and arms, and reverberates throughout the center
plates, affecting both mechanical and electrical systems along the way. Although the
logical conclusion suggests that maximizing the number of dampened connections within
the assembly will minimize the vibrations, the slight angular imbalance that a damping
device would produce when placed between motor and motor mount or between arm and
center plate is extremely undesirable: the increased chance for an unstable flight is not
worth the slight reduction in vibration. Therefore, serious precaution must be taken when
determining which areas require dampening and which can be left rigid.
For example, a SECRAFT anti-vibration O-ring damper (as depicted in Figure 2.13)
is an original design consideration used to isolate the upper and lower center plates from
the arms.
Figure 2.13: SECRAFT anti-vibration damper considered for vibration reduction
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Although this part would greatly diminish the vibration seen by the center plates, the
incorporation of this component in the design would cause arm deflection with respect to
the reference frame even at hover, causing thrust to be wasted and efficiency to be
sacrificed (it is an absolute requirement that the direction of thrust remain orthogonal to
the reference plane of the frame). Instead of including these dampers and mounting the
controller directly onto the center plate, the arms are bolted between upper and lower
center plates and the controller is isolated on an entirely separate plate. This plate receives
its own damping with the cylindrical rubber dampers shown in Figure 2.14 below; these
separators insulate some of the vibration passing through the center plate and relieve the
controller of any unwanted impact forces from an improper landing for a significantly
decreased cost as compared to the SECRAFT damper
Figure 2.14: Cylindrical rubber damper selected for vibration reduction of controller
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As a supplement to the cylindrical mounts, RTOM Moongel will be used to adhere
the controller to the polycarbonate controller plate. These pads are sold commercially for
drum pads, but have been proven to isolate vibration much better than alternative foam
adhesives and are less complex to implement and maintain than O-ring suspension
structures.
The camera mounting apparatus is another location within the assembly where
vibration reduction is key. Although custom solutions are considered for the design of the
mount, an off-the-shelf solution is the selected method. Construction of a custom camera
gimbal would not only require 2-axes of rotational freedom (necessitating two separate
servo motors), but would also involve a camera holster and a damping system to reduce
camera vibration. Overall, the cost of this type of custom equipment is not an efficient use
of budget, since cost-effective, reputable camera gimbals are readily available on the
market. These gimbals are designed to reduce the “jello” effect commonly witnessed in
first person video applications, and can satisfy vibration reduction with a single
mountable apparatus.
A final effort to reduce the detrimental effects of motor vibration is the use of
Threadlocker on each nut and bolt. Although this will not significantly reduce vibration
through the frame, application of Loctite Blue will prevent unscrewing of the components
that hold the frame together while allowing for maintenance if necessary.
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Chapter 3: Power
In order to be operational, this quadcopter requires a power source and a method of
distributing power throughout the system to its many components. Due to the nature of
the project and its operation, this source obviously can not be stationary on the
ground. Therefore, a battery must be selected that will meet all of the functions and
requirements each individual subsystem needs, along with the overall specifications of
the quadcopter. This includes the flight time, the current draw of electrical components,
and the power supplied to the motors. In order to correctly distribute power throughout
the quadcopter, electronic speed controls (ESC’s) and voltage regulators must be used.
Section A: Battery Selection
Selecting an operational battery for use on this quadcopter is an iterative process with
the motor selection. Because each individual motor draws a large amount of current, a
battery must be selected that can safely support the combined current draw of the motors
and all other electrical components on the quadcopter. In order to do this, the first thing
determined was the combined current draw of the entire system, which came out to 67.73
A. In order to operate safely, we decided that the battery selected must match this current
draw with a safety factor of at least 2. Therefore, the battery selected must support 135.5
A of current draw throughout the system.
Component Motors Video Transmission
Telemetry Sensors Controller/GPS Total
Current Draw
(Amps)
16.8 (each)
.05 .02 .035 .11 67.73
Fig. 3A.1: Current Draw of Individual Quadcopter Components
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The battery must also be able to support the system throughout the entire flight time
spec, which is set at 15 minutes. This means that for consisted mixed flight, which is at
approximately 75% throttle, the battery must be able to safely supply power to the system
for 15 minutes. In order to calculate the estimated mixed flight time, we must first figure
out the total current draw of the quadcopter at 75% throttle. From the motor data sheet,
it can be seen that during mixed flight, the motors are drawing approximately 10A each,
making the total system current draw 40.77A. In order to find flight time, we divide the
capacity of the battery (10 Ah) by the total current draw of the system. We then multiply
that number by 60 minutes to give us our estimated flight time. Below, you can see our
calculation.
Flight Time = (Capacity/Current Draw)*60 (Eq. 3.1)
10/40.77=.2453 , 60 * .2453=14.72 min=14 min 43 sec
As you can see, our battery can adequately provide enough power to the entire system for
nearly the entirety of our goal flight time of 15 min. Here, you can also see our estimated
flight times if the motors were run at different throttle percentages for the entirety of
flight.
Throttle 50% (Hover)
65% 75% (Mixed)
85% 100%
Current Draw (Amps)
3.8 7.4 10 13.5 16.1
Estimated Flight Time
37 min 35
sec
19 min 46
sec
14 min 43
sec
10 min 58
sec
9 min 13
sec
Fig. 3A.2: Quadcopter Flight Times based on Constant Throttle
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Section B: ESC’s and Voltage Regulator Selection
As mentioned previously, Electronic Speed Controllers (ESC’s) and voltage
regulators help determine how much power is provided to each component of the
quadcopter. While the battery may have a nominal voltage of 14.8 volts, not every
component on the quadcopter is made to handle that much voltage. Therefore, we need
voltage regulators to limit the amount of voltage that reaches the input of certain
components. There are 3 different voltages that components on the quadcopter operate
at. As you can see in figure 3B.1, those voltages are 5 V, 12 V, and the 14.8 V coming from
the battery. Custom voltage regulators will help us achieve the needed voltage input at
each of these components. While linear voltage regulators are the simplest form of
regulator, we will be looking into the use of switching regulators. Linear regulators
operate by taking the difference between the input and output voltages and burning it up
as heat waste. Because there are large differences between regulator input and output
voltages on this quadcopter, a large amount of waste heat energy would be produced,
meaning a low efficiency of the regulators themselves, along with the need for additional
bulky heat sinks, which would reduce the battery life of the copter.
Switching regulators work by taking small amounts of energy, bit by bit, from the
input voltage source, and moving them to the output of the voltage regulator. The energy
losses are relatively small in moving energy in this fashion, and the result is a much higher
efficiency than that of a linear voltage regulator. Since switching regulator efficiency is
less dependent on input voltage, they can power useful loads from higher voltage
sources. A basic diagram of a switching regulator can be seen below in Fig. 3B.2. When
the switch is closed, the inductor will begin to generate an electromagnetic field, and the
diode will act as an open circuit, for it is reverse biased. When the switch is opened again,
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the inductor field will discharge and produce a current, causing the diode to conduct until
discharge is complete. The value of the inductor determines the minimum load
requirement of the regulator. If this value is not met, the regulator will not function
properly and may even be damaged.
Quadcopter Components
Multiwii AIO Flight
Controller
800 mW Transmitter
Motors Ultrasonic Sensors
3DR Radio Telemetry
Operational Voltage
5 V 12 V 14.8 V 5 V 5 V
Fig. 3B.1: Operational Voltage of Quadcopter Components
Fig. 3B.2: Basic Switching Regulator Circuit
Our motors, on the other hand, need a different form of input regulation. Our
ESC’s will control how fast each motor will be spinning during flight, based off of
controller commands and coded in constraints. Essentially, each ESC works currently by
receiving commands from a physical ground controller. From there, each ESC will send
a PWM (pulse-width modulated) signal to the motors, controlling the speed of each motor
individually. Essentially, each pulse width of the signal being sent from the ESC’s
corresponds to a certain motor speed. If the pulse width is increased, the speed at which
the motor turns is increased.
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Chapter 4: Communications
With a project of this nature, a well performing system of communications is of the
utmost importance. The microcontroller, besides its own internal data flow, must send
that data to the base station for monitoring, and receive data from it (our remote
commands). All the while, the flight controller must be receiving and outputting reliable
signals to the electronic speed controllers, so that flight remains stable and smooth. An
added layer of complexity is the inclusion of a live video feed, despite it being a separate
sub-system. A basic, high level diagram follows:
Figure 4.1: System Level Communications Diagram. Solid lines represent hard wired
connections, and dotted lines represent wireless connections
This diagram, while providing useful information, is very high-level, and it is important
to take a much closer look at the system for a thorough analysis. It can be broken up into
four different sections (A-D). One is the on-board and hard wired data, coming from
sensors and GPS (A). The second is the telemetry link, for transmission and reception of
important flight data and controls from board to base station, and visa-versa (B). The
third is the video feed, as, from a system perspective, it does not interact with anything
on-board the quadcopter (C). The final section is the manual controls and overrides (D),
and all are detailed through the next few pages. A much more detailed and less abstract
data flow diagram is included in figure 4.2, which will be referenced in each section.
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Figure 4.2: Detailed Data Flow and Communications Diagram
Section A: On Board Data Flow
The on-board flight controller is ATMega 2560-based, and operates with a 16MHz
clock rate. This is important, as we are integrating additional sensors to those already on-
board. Internally, the controller includes a 6-axis gyroscope, accelerometer, altimeter,
and magnetometer. The gyro provides pitch/roll/yaw information, which is made more
precise with the magnetometer (it prevents the gyro readings from “drifting” over time).
The accelerometer provides, trivially, information on instantaneous acceleration (of three
axis, pitch/roll/yaw), and the altimeter provides altitude. All these sensors provide their
data through the use of an on-board, expandable, I2C bus. We are integrating an external
ultrasonic sensor to this bus, as well, to be used for object avoidance. Every sensor used,
and the board itself, supports the “Fast” I2C data rate, which is 400kHz. This was shown
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in figure 4.2 by the green lines of “fast I2C” sensor data. The performance (time constants,
latency, processing, etc) of the controller and sensors is explained further in chapter 5.
Also included in the flight controller is the capability to add a GPS module,
something that is integral to the success of our project. The interfacing is done through a
serial (RS232) connection, shown in figure 4.2, with a 10Hz update rate. It was originally
thought that the video transmitter, operating at 1258MHz, would cause interference to
the GPS, making it more difficult to obtain a lock. This did not turn out to be true, as the
commercial GPS we are using only utilizes the “L1” frequency of 1575MHz, not the
theoretically troublesome L2 frequency of 1228MHz, as the L2 frequency is reserved for
military use.
Section B: Telemetry
The transmission of data to and from the flight controller and base station software
is accomplished through the use of a dedicated telemetry link. It uses the 433MHz
frequency, a part of the 70cm ameteur radio band. This frequency, without an ameteur
radio license, is illegal to use. Team leader Daniel Worts (author of this chapter), however,
possesses this license, call sign KD2HJY, thus allowing the team to take advantage of this
frequency; it provides tremendous range and object penetration improvements when
compared to the other popular telemetry frequency, 915MHz. We will be using a low pass
filter on the on-board end of the telemetry link, in order to filter out the potentially
problematic second and third harmonic interference to any 915MHz systems in the area
and to our 1.3GHz video transmission, respectively. This filter was designed to pass 100%
signal strength at 433MHz, while attenuating the signal -40dB (1% strength) at 915MHz
and -60dB (0.1% strength) at 1258MHz.
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Making use of an online calculator and PSpice, it was determined that a
butterworth filter did not provide adequate performance, and a Chebyshev model was
chosen. The required filter order was experimentally determined to be N = 7, and the
passband ripple was set to be 0.05dB, the minimum value that still met design
specifications. The resulting design is shown in figure 4.3, with the simulation results in
figures 4.4 (linear scale) and 4.5 (log scale).
Figure 4.3: Telemetry Low Pass Filter Design, N=7, Chebyshev
Figure 4.4: Frequency Sweep, Linear Voltage Scale (Y axis), showing 100% (peak of
ripple) signal strength transmission at 1258MHz
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Figure 4.5: Frequency Sweep, Log Voltage Scale (Y axis)
To realize this filter, the following components will be used. They will all be
purchased from Digi-key.
Component Value Tolerance Rated V/I Part Number
C1 = C4 6.0pF +/- 0.25pF 50V 445-5036-1-ND
C2 = C3 11pF +/- 5% 50V 490-1404-1-ND
L1 = L3 20nH +/- 5% 550mA 490-6873-1-ND
L2 24nH +/- 5% 500mA 490-6878-1-ND
Table 4.1: Telemetry Filter Components
The telemetry kit uses a standardized format for sending data, called MAVlink
(Micro Air Vehicle Link) Protocol Framing. This protocol sends (and receives) data
through the use of six standardized bytes (zero through five), then the data (a variable
amount of bytes), and lastly a checksum byte, to ensure data integrity. The following table
(4.2) describes the MAVlink data format, where n denotes the byte index.
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Name
Byte Index Purpose
Start 0 Represents the start of data (frame) transmission
Length 1 Represents the length of data (payload)
Packet Sequence 2 Allows for detection of data loss
System ID 3 Identifies the originating “sender” (unchanged for us)
Component ID 4 Identifies the component sending data (i.e. the IMU)
Message ID 5 Identifies how to decode the specific payload type
Payload 6 to n+6 The data in the message
CRC n+7 & n+8 Checksum of the packet
Table 4.2: MAVLink Data Format
The MAVLink format would not be so useful were it not also supported by our
ground station software. That is to say, the software also knows how to interpret the type
of data, where it is coming from, what it actually is, and how to display it on-screen in a
format familiar to humans. This is the same way we will be sending commands - by using
the software, which frames our data in MAVLink protocol, where it is easily received and
interpreted at the microcontroller. Remote commands will consist of GPS waypoint
destination updates and on-the-fly flight mode switching. The specifics of flight modes
are detailed in chapter 5 (software).
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Section C: Video
There are many options available to implement a wireless, live video feed, but few would
fit our design requirements. The commonly used frequencies for video transmission, as
defined by the FCC, are 900MHz, 1.3GHz, 2.4GHz, and 5.8GHz. There are further
limitations in each of these frequencies for power output, and, just as with our telemetry
frequency of 433MHz, some require an ameteur radio license to use. Again, because team
leader (and current chapter author) Daniel Worts has this license, the team is provided
with a more robust set of options. In weighing these options, the main considerations for
us included range and potential interference, as well as practicality. The commercial
availability of video transmitters/receivers ruled out 900MHz, and 1.3GHz was chosen
for it’s superior range and object penetration properties. In addition, the size of high gain
antennas for 1.3GHz is reasonable enough (in terms of real estate) to fit on the
quadcopter. 2.4GHz and 5.8GHz do not provide sufficient video range, and 2.4GHz is
used as our manual control frequency (see section D). Figure 4.6 shows a block diagram
of the system, which is a more detailed version of the right three blocks in Figure 4.2.
Figure 4.6: Video Feed Block Diagram
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The specific high gain antennas chosen were done so based upon polarization and size.
It was determined that circular polarization provided the optimal signal propagation, as
linear polarization would not be sufficiently maintained through the movement and
tilting of the quadcopter. Circular polarization can be left or right handed, and right
handed was chosen, because it had more commercially available antennas. The final
chosen antenna for video transmission is a three-lobe cloverleaf, which pairs very nicely
with the final choice of receive antenna, a five-lobe skew-planar. It would be a senior
project in and of itself to design this video transmission and reception system, including
the antennas and analog to digital (USB) convertor, from the ground-up, so we had to use
commercially available components for all. Though we will only be able to display
720x480 resolution from the live feed, due to USB 2.0, analog to digital conversion, and
price limitations, we will still be storing the full 1920x1080p HD video on a micro SD card
inside our camera.
Filtering the video transmitter output is necessary to suppress harmonic interference
with our 2.4GHz transmitter. A number of options were weighed, and, ultimately, it was
decided that a low pass filter would be created by the team (Figure 4.7). The first and
major design consideration is the attenuation provided at 2.4GHz. This was defined to be
60dB, which corresponds to a 100x drop in signal strength. This specification was utilized
in order to find the order filter needed, as well as the type. Because it provides steeper roll
off, a Chebyshev model was used. The 3dB cutoff point was set to be 1460MHz, which
allows for full strength signal transmission at 1258MHz (with respect to ripples), and the
passband ripple was set to be 0.2dB. This provided realistic component values, as well as
a minimum loss in signal strength with varying component values due to tolerances. The
order filter to provide 60dB of attenuation at 2.4GHz was found to be N=9. The filter
schematic is shown in figure 4.7, with frequency sweeps shown in figures 4.8 (linear) and
4.9 (log, to display 60dB drop). The output was normalized to be 1 volt maximum to make
observation simple.
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Figure 4.7: Video Low Pass Filter Design, N=9, Chebyshev
Figure 4.8: Frequency Sweep, Linear Voltage Scale (Y axis), showing 100% (peak of ripple) signal strength transmission at 1258MHz
Figure 4.9: Frequency Sweep, Log Voltage Scale (Y axis)
A simulation was also done to see the behavior change of the filter with varying
component values, in order to confirm function with realistic capacitor and inductor
tolerances. All values were increased by 10%, and, observing figure 4.10, it can be seen
that the vital characteristics remained functionally unchanged.
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Figure 4.10: Frequency Sweep, Linear Scale (Y axis), All Component Values +10%
To physically construct this filter, the following components will be utilized. They will
all be purchased from Digi-Key. Reasonably priced, available, and sufficiently rated
inductors could not be found for L1 and L4, but, by using a parallel combination of two
15nH inductors, the needed values will be achieved.
Component Value Tolerance Rated V/I Part Number
C1 = C5 3.0pF +/- 0.1pF 250 Volts 712-1347-1-ND
C2 = C4 5.0pF +/- 0.1pF 50 Volts 1276-2129-1-ND
C3 5.1pF +/- 0.25pF 250 Volts 712-1359-1-ND
L1 = L4 15nH (two in parallel)
+/- 5% 1.1 Amps (2.2 together)
535-12231-1-ND
L2 = L3 8.3nH +/- 5% 1.5 Amps 490-7682-1-ND
Table 4.3: Video Filter Components
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Section D: Manual Controls and Overrides
Before the team can implement autonomous navigation, we must have basic manual
controls functioning; one must walk before they can run. A bound 2.4GHz, 6-channel
transmitter and receiver is being used for this. Because of our telemetry and video, lower
frequencies were not an option, and 2.4GHz is by far the most commonly used for radio
control vehicle controls. That is not to say that it was not a design consideration - the
2.4GHz system provides enough range, should controls need to be taken over mid-flight
(due to some unforeseen software or electro-mechanical failure), and there are no
interference issues.
The four primary channels of the transmitter/receiver are defined as throttle,
elevator, aileron, and rudder. The last two “auxiliary” channels are simply switches, which
will be used for selection of manual or autonomous flight, and parachute deployment.
Each channel of the receiver is wired to it own serial input pin on the flight controller,
which interprets and processes the input of every channel (when in manual mode), and
sends the corresponding pulse-width modulated signals to the electronic speed controller
of each motor. The manual, four-channel input is the equivalent to the data given by the
on-board sensors. More detail about the ESC operation was provided in chapter 3, and
more detail about the flight controller processing is included in chapter 5. Figure 4.2
displays the (color-coded) differences in input to the controller when in autonomous
versus manual mode.
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Chapter 5: Software and Controller Hardware
Section A: An Introduction to the Role of Software in the Autonomous Quadcopter
Given that one of the primary specifications in the design of the quadcopter is for it to
be autonomous, software plays a major role in that all flight controls and navigation must
be computed and applied via software and not through a manual controller. That being
said, there are multiple levels of software and controls to be discussed in this
section. First, an introduction and description of the open-source softwares to be used in
the project will be given in the next section. Open-source softwares are being used for
both the flight controller and the ground station. This includes a description of the
software interfacing of the information passed via telemetry, which is discussed in
Chapter 4, Section B.
Next, an in-depth explanation of the flight controller will be given at both the
hardware and software level. The flight controller includes multiple loops that run on
different timers. The operations controlled on each these timers will be described in order
of the fastest timer to the slowest. Once that is done, the current status of the software
programming and interfacing will be given.
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Section B: Open-Source Software
As was mentioned in the previous section, there are two levels of open-source softwares
being used in this project. The first level exists at the flight controller level and is used to
manage all in-flight input from the sensors and gyros, receive GPS inputs from the ground
station, and relay information back to the ground station. This open-source software is
called MegaPirateNG and is built on-top of another open-source software called
Arducopter which is a flight control manager built for Arduino. The functionality of this
software will be discussed in greater detail in the next section.
Figure 5.1 - Software Interfacing between Mission Planner and the Flight Controller.
As for the ground station, a graphical user interface (GUI) called Mission Planner
(also by Arducopter) is being used. This program provides widgets for monitoring the
status of the flight, and a built-in map to view the GPS location of the vehicle. In addition,
waypoints can be passed from the ground station to the flight controller to provide
navigation points in the flight path. This communication is done through a packing C-
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structs via a serial protocol called MAVlink. The interface between the ground station
and the quadcopter can be seen in Figure 5.1. The ground station maintains a C++ style
object for each quadcopter in the air (in this case, only one) and uses information relayed
from the vehicle to keep the object up to date with all of the latest
information. Furthermore, the ground station communicates back to the flight controller
with GPS waypoints. Through the MAVlink protocol, it can write a waypoint, read and
clear the current one, and query to determine if it has reached its current waypoint. These
waypoints can be updated in real time through the GUI that the software provides.
Section C: Flight Controller and Sensor Performance
With any program that is written for the arduino platform, the main file consists of two
functions from which all other functionality is derived Figure 5.2. The first function that
is processed and ran is the the setup() function. In most cases, this function will be
used to allocate memory, initialize the required global variables, and any other
initialization processes that are necessary. In the case of the flight controller software,
the setup function populates the arduino’s memory with the initial variable values and
establishes the power sources from the battery or power supply to the board. The final
function performed by the setup function is to call the second major function in the main
file, loop().
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Figure 5.2 - Basic arduino file setup
As the name implies, the loop function is an infinitely running loop that is used to
contain the main functionality of the arduino board. The contents of this function is
entirely application dependent and will therefore vary with the desired output of the
arduino. Obviously, in this case, the desired output of the arduino is to fly and navigate
the quadcopter. When considering everything that goes into the autonomous flight of a
vehicle, this amounts to a large number of processes. To manage this, the functions are
divided into separate functions and loops that run on different timers. These different
timers run at different speeds to give more processor time to certain functions and
schedules others at a slower rate. A high level overview of these timers and the controls
they process can be seen in Table 5.1.
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Timer Loop Name Speed (Hz) Controls
timer 0 (pin 13, 4) fast_loop() 100 - process any deferred messages - PWM motor controls - inertia calculations - roll, pitch, and yaw
timer 2 (pin 10, 9) fifty_hz_loop() 50 - read/adjust altitude - update throttle output - sonar (if enabled)
timer 1 (pin 12, 11) medium_loop() 10 - GPS and compass - navigation update - battery monitor
timer 3 (pin 13, 4) slow_loop() 3.33 - camera
timer 4 (pin 5, 3, 2) super_slow_loop() 1 - various logging - auto power down
Table 5.1 - High Level Overview of Flight Controller Software
The loop titled fast_loop() is actually the main loop of this arduino software.
As Table 5.1 indicates, this loop handles many of the main flight controls just as adjusting
for changes in the roll, pitch, and yaw and updating the outputs to the PWMs which
directly control the motors. Since this loop contains the main functionality of the system,
it is up to this loop to schedule the other tasks not found in this control loop. The way this
works in the software is that, once the fast loop has completed an iteration, it will “tick”
the scheduler to and assign any functions that are due to run. Figure 5.3 gives information
regarding how often each function should run. Once this is done, the first task of the fast
loop the next time it runs is to completed any scheduled tasks. This ensures that all tasks
are being performed and is not starved for too long.
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Figure 5.3 - Processes scheduled by the fast loop. The value in the 0 index is the function name, index 1 indicates how often they should be run, and index 2 is an approximation
of the run time
Section D: PID Software Implementation
The previous section in this chapter discusses the multiple timers and the functions on
those timers that the microcontroller on the quadcopter uses to update both its position
in space and its orientation in the air, otherwise known as the roll, pitch, and
yaw. Whenever there is an operation to be performed that involves adjusting the system
from a current measurement to a new, desired measurement, an appropriate technique
to employ is PID control. PID stands for present (or proportional), integral, and
derivative error and can be used by the quadcopter to achieve stability. In terms of said
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stability, “error” refers to the difference between the current roll, pitch, or yaw angle and
the desired values for each. Before going into how the software implements PID control,
a more in-depth description is appropriate.
The basic equation for PID control is given by:
Response = KpP + KiI + KdD
where the ‘K’ values represent the coefficients to the proportional, integral, and derivative
errors, respectively. By tuning these coefficients, the importance of each error can be
altered in the system. The proportional gain coefficient, Kp, uses the present error in the
algorithm. The higher this coefficient, the more sensitive or loose the quadcopter will feel
to angular change. Oppositely, the integral gain coefficient, KI, is a weighted accumulation
of the past error in the system. Ideally, if, say, the yaw is tilted by 10 degrees, the integral
gain will be able to reproduce the reverse of that and adjust the yaw 10 degrees in the
opposite direction. Therefore, tuning the integral gain higher is good for handling
irregularities in the flight such as strong winds, however, for a mostly stable flight, the
integral coefficient is hardly necessary. Lastly, the derivative coefficient, Kd, measures the
rate at which the error is changing, which is why it is called the derivative factor. It is
sometimes called the acceleration parameter because it uses the current rate at which the
error is changing to predict the future error and make changes based on that rate. Figure
5.4 shows a diagram of the PID control loop with the input from the sensors divided into
its P, I, and D parts all going into the microcontroller which contains the control
algorithm.
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Figure 5.4 - PID Control Loop implemented on the quadcopter for the roll, pitch, and yaw of the flight.
It was previously mentioned that PID control can be used to achieve flight
stability. Stability refers to the steady, as opposed to erratic, adjustment of the roll, pitch,
and yaw of the quadcopter. Roll, pitch, and yaw represent the three angular axes in 3D
space. If the quadcopter is flying straight forward, roll is the front-to-back angle, pitch is
the side-to-side tilt, and yaw is the title along the vertical axes stemming out of the
ground. Because the desired output of the system can be broken down into desired values
for the roll, pitch, and yaw individually, each parameter will have its own PID control and
their own three coefficient. However, since quadcopters are designed to be completely
symmetric, the coefficients should be the same across each axis.
It has already been discussed that the roll, pitch, and yaw are updated in the
fast_loop() of the microcontroller which runs at 100Hz. It is important that this runs
on this loop because the more often that inputs from the sensors are read and received by
the controller, the faster the PID algorithms can update. A commented example of the
this process, for the roll specifically, can be seen in Figure 5.5
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static int16_t get_rate_roll(int32_t target_rate) { static int32_t last_rate = 0; // previous iterations rate int32_t p,i,d; // used to capture pid values for logging int32_t current_rate; // this iteration's rate int32_t rate_error; // simply target_rate - current_rate int32_t rate_d; // roll's acceleration int32_t output; // output from pid controller int32_t rate_d_dampener; // value to dampen output based on acceleration
// get current rate current_rate = (omega.x * DEGX100);
// calculate and filter the acceleration rate_d = roll_rate_d_filter.apply(current_rate - last_rate);
// store rate for next iteration last_rate = current_rate;
// call pid controller rate_error = target_rate - current_rate; p = g.pid_rate_roll.get_p(rate_error); i = g.pid_rate_roll.get_i(rate_error, G_Dt); d = g.pid_rate_roll.get_d(rate_error, G_Dt); output = p + i + d;
// Dampening output with D term rate_d_dampener = rate_d * roll_scale_d; rate_d_dampener = constrain(rate_d_dampener, -400, 400); output -= rate_d_dampener;
// output control return output; }
Figure 5.5 - Software implementation for PID control of the roll axis
The software example in Figure 5.5 implements what has just been discussed when
describing PID control. It defines the error has the difference between the current rate
and the target rate, and then uses that to obtain values for P, I, and D. To do so, it calls
the functions get_p(), get_i(), and get_d() which are part of an accessory PID
library. The coefficients for each part are built into the library as static variables and can
be adjusted as needed. From there, it gets the output value by summing up the P,I, and
D and then dampens (or accelerates, but usually dampens) it based on the differential
component which, again, uses the current rate of change to predict the future
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error. Lastly, it simply returns the output value. This is done for the roll, pitch, and yaw,
all of which happen one time in the fast loop which operates 100 times a second.
Section E: Current Status of the Software
At this point in the construction process, the flight controller has been programmed
with the MegaPirateNG software, which was first manually configured to work with the
sensors, GPS, and telemetry kits located on the board. With that complete, a MAVlink
connection from the flight controller to the ground station was able to be established via
a USB cable. With the MAVlink connection, sensor inputs were able to be read and
transmitted to Mission Planner, which uses this data to update the graphical user
interface with the row, pitch, yaw, and altitude of the flight controller. The GPS has not
yet been interfaced.
As for the next step in the construction and testing process, it will be to replace the USB
cable connection with that of the telemetry connection so that wireless communication
can be established to transmit the same sensor data to Mission Planner. From there, the
GPS module can be interfaced with the flight controller to provide that location
information as well. The final steps in terms of the flight controller will be to supply power
to it from the on-board battery and to connect the PWM outputs to the motors and begin
tuning and testing the flight of the quadcopter. This will be done by tuning the PID
coefficients described in the previous section of this chapter. Since it would be difficult
to mathematically represent the quadcopter exactly as it performs, the best way to do this
is through a trial-and-error process of tuning the coefficients and examining how it
responds to control signals. This tuning will be done using the RC controller so that the
correct coefficients are in place for the autonomous flight.
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Chapter 6: Conclusion
Although the group is slightly behind according to the semester goals set by the
preliminary schedule, significant progress will be made over the months of December and
January to ensure that a functioning quadcopter is ready for testing and tweaking by the
beginning of next semester. This progress involves assembling the entire frame, testing
all necessary equipment for conformance to manufacturer specifications, integrating all
mechanical and electrical components, and making headway on software
implementation. Due to the fact that the Autonomous Quadcopter Senior Project is a
relatively new venture at The College of New Jersey, with a somewhat unsuccessful
history, diligent testing and performance analysis must be completed to maximize the
potential for a stable flight and reliable integrated design to, ultimately, achieve success.
With projects of this nature, it is reasonable to assume that slight modifications in design
and implementation will be called for along the way; the proper steps will be taken to
guarantee prompt completion of open action items so that the testing phase of the project
can begin.
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List of References
1. A Beginner’s Guide to Switching Regulators,
https://www.dimensionengineering.com/info/switching-regulators
2. A Survey of Quadrotor Unmanned Aerial Vehicles,
http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6196930&url=http%3A
%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6196930
3. Antenna Design, http://www.microwaves101.com/encyclopedias/antenna-design
4. Autonomous quadcopter swarm robots for object localization and tracking,
http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6710447&url=http%3A
%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6710447
5. Decibel Conversion, http://www.mogami.com/e/cad/db.html
6. Five Surprising Drone Uses (Besides Amazon Delivery),
http://news.nationalgeographic.com/news/2013/12/131202-drone-uav-uas-
amazon-octocopter-bezos-science-aircraft-unmanned-robot/
7. IRIS+, http://store.3drobotics.com/products/IRIS
8. Low Pass Filter Calculator,
http://highfields-arc.co.uk/constructors/olcalcs/lpf.htm
9. PID Controller Tutorial for Robots, http://robot-kingdom.com/pid-controller-
tutorial-for-robots/
10. Quadcopter Dynamics,
http://nbviewer.ipython.org/github/pestrickland/notebooks/blob/master/quadc
opter_dynamics.ipynb
11. Quadcopter Dynamics and Control, Randal W. Beard,
http://rwbclasses.groups.et.byu.net/lib/exe/fetch.php?media=quadrotor:beards
quadrotornotes.pdf
12. Quadcopter Flight Dynamics, Mohd Khan,
http://www.ijstr.org/final-print/aug2014/Quadcopter-Flight-Dynamics.pdf
13. Quadcopter PID Explained and Tuning, http://blog.oscarliang.net/quadcopter-
pid-explained-tuning/
14. Radio Frequency Safety, http://www.fcc.gov/encyclopedia/radio-frequency-
safety
15. Radio Spectrum Allocation, http://www.fcc.gov/encyclopedia/radio-spectrum-
allocation
16. RTF XPX Heavy Lift Quadcopter with GPS,
http://xproheli.com/collections/multirotors/products/xpx-heavy-lift-quadcopter
17. Switching Regulators, http://www.linear.com/products/switching_regulator
18. Unmanned Aircraft Systems, https://www.faa.gov/uas/
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Appendix A: About
Appendix A1: Bio
(Left to Right) James Rottinger, Benjamin Kushnir, Daniel Worts, Jordan Freedner
Daniel Worts is the team leader of the autonomous
quadcopter and one of two electrical engineers on the team.
He is primarily responsible for all of the RF communication
used on the vehicle and much of the mechanical/electrical
interfacing. Because of his experience, he is also leading the
electrical assembly. Outside of this project, he is very
actively searching for a full time job as an entry level
electrical/RF engineer.
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James Rottinger, computer and software engineer, is
responsible for all software and computing components on
the quadcopter. This includes programming and
configuring the flight controller, the ground station, and the
interfacing of telemetry kits to both. Outside of this project,
he works as a software developer for the San Francisco based
start-up, Weebly, which he will be joining full-time upon
graduation in May.
Benjamin Kushnir is the mechanical engineer of the
team, responsible for frame design and structural analysis
of mechanical components. He is tasked with creating a
model of the entire assembly, construction of all mechanical
subsystems as well as motor/propeller selection. Alongside
this project, he currently works as a part-time Process
Engineer at a performance plastics facility, which he hopes
will progress into a full time position.
Jordan Freedner is the other electrical engineer and is
primarily tasked with creating a power system for the
project, along with electrical-mechanical
interfacing. Outside of this project, he is actively searching
for a full-time position as a power systems engineer.
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Appendix A2: Realistic Constraints and Engineering Standards
Like any proper engineering endeavor, it is required that a set of standards and
constraints be identified and followed to certify a safe, economical, and ethical design that
will uphold the expectations of the user and observer. Although design constraints are the
first to be considered, these are detailed throughout the entire report and are therefore
not covered in this section. Instead, this section will discuss how the design is affected by
all other decisions that are made through the process.
In terms of importance, safety constraints are by far at the top of the list with a
project of this caliber. It is essential to understand the safety considerations with regards
to design and testing that must be made with any vehicle, especially with one that will be
flying overhead. On top of a reliable, rigid design, various fail-safes are incorporated into
the assembly to minimize the chance of the quadcopter falling out of the sky, such as a
battery voltage monitor to signify low power, and ultrasonic object avoidance sensors that
allow quick route correction in case of an unexpected obstacle. As a last resort, a
parachute operating on a separate power source will be deployed in case of severe
malfunction. These various safety constraints will provide reassurance to the user as well
as to those that are observing the flight of the quadcopter. Safety in regards to testing will
be maintained by ensuring that the software dictating autonomous control is entirely
functional before autonomous testing begins, and all initial testing will be conducted in
an open field, at very low altitude.
With green engineering experiencing a sudden increase in popularity, it is
important to understand the constraints that the environment places on the design and
operation of the quadcopter. Although the quadcopter is fully battery operated and
therefore uses no natural gas energy source, an important consideration to keep in mind
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during design is noise pollution. The motors are the main source of noise during the flight
of the vehicle. With that in mind, the motor selection process includes noise as a decision
factor, although thrust production and expected flight time are both factors that hold a
much greater influence. Eventually, a motor was selected that will minimize the noise
levels (with more noise usually comes more vibration, which is another serious design
constraint). This motor is certainly not the cheapest, but is well worth the advantages that
it offers.
The social and ethical aspects of any drone design is a highly debated topic,
especially with current-day UAV design becoming so technologically advanced. Freedom
of flight is a large concern in regards to ethical constraints; a considerable argument
against UAV production is the idea that they cause an invasion of privacy, especially when
the vehicle has a camera that offers live video feed. The group wants to clarify to the public
that any footage taken will not be utilized for commercial applications, and any recorded
video that includes bystanders will only be used with the consent of those recorded.
Additionally, the path of the quadcopter will deliberately avoid all residence halls (and
highly traveled areas), as it would not be a pleasant sight for a resident to see a vehicle
with a camera hovering outside his or her window.
Maintenance and repairability are important constraints to consider for both
mechanical and electrical construction. In terms of mechanical design, it is important that
the quadcopter has easily removable parts in order to perform maintenance on parts if
necessary. Although weight is a serious concern, the design will not compromise strength
for weight, since it is more reasonable to introduce a stronger, heavier design than for the
frame to be too delicate and require continuous repair. In terms of electrical design, the
wiring system must be organized and clearly accessible at all areas. Additionally, the
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design must include proper insulation where necessary in order to avoid short circuiting
and interference.
Besides holding all constraints in mind, the final design must also comply with all
standards and specifications provided by the Federal Aviation Administration (FAA). The
FAA requires that all nonmilitary UAV’s be flown under a 400ft altitude and operate
during daytime only. Although autonomous, the quadcopter must be in sight at all times,
meaning the team will have to follow the vehicle during operation. Finally, the quadcopter
cannot enter any airport fly zones and must not be operated for commercial use.
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Appendix B: Management
Appendix B1: Gantt Chart
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Appendix B2: Meeting Minutes
9/19/14: Need to form a high level system diagram and better gantt chart
9/24/14: Need better articulated top level specifications, specific roles, and design
challenges, and more knowledge in control theory
9/28/14: Order forms filled out for controller, telemetry, gps module, electronic speed
controls. Wiring sizes as per current draw chosen
10/7/14: Communications systems and electrical hardware/tools material list and order
forms done. Finalized top level specifications and design challenges. Noted that GPS
should be separated from video transmitter. Finalized a budget for meeting with Dean
Schreiner.
10/9/14: After first budget meeting with the Dean, it was determined that we required a
more integrated design, more safety measures, a better defined wiring plan (grounding),
and a solution to possible GPS interference
10/11/14: Professor Joseph Jesson cleared up a misconception about the operation of the
GPS - the team was concerned about interference with the L1 GPS frequency, 1228MHz,
which is only used by military. The L2 frequency, 1575MHz, is the only one actually used,
and it will not be harmfully interfered with.
10/15/14: Proposed the idea of a parachute recovery system. Noted a higher discharge
battery is required, as well as motors with larger lift, and that a 2.4GHz 6-channel
transmitter/receiver set must be budgeted for/ordered.
10/18/14: Better integrated electrical and mechanical design on SolidWorks model,
decided to custom make a parachute recovery system, chose 2.4GHz Tx/Rx
10/21/14: Had second budget meeting with the Dean. Very close to being approved, but
we need to do a bit more analytics. Specifically, dynamics calculations to validate design
specifications, time constant/sensor latency calculations, and better validated power
useage.
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10/28/14: Brought together and verified all analytical work, including: forward
speed/angle, maximum speed, battery life with respect to thrust percentage, sensor
latency and control loop computation time, and communication range. Established agile
development-style management using the website Trello.
11/3/14: Third budget meeting with Dean Schreiner - budget was approved (third time’s
a charm!)
11/9/14: End of the first agile development “sprint,” had to carry some tasks into the new
“sprint,” namely, a blog post from Jim, Jordan, and Ben, getting Jordan and Jim machine
shop approved, and filling out the “about” section of our website. Defined the tasks for
“Sprint 2,” 11/9 through 11/25, which included: frame design finished, 100% completed
and verified power system design, controller interfaced to base station software, and
manual controls interfaced from receiver to ESC’s to motors (as well as calibrated ESC’s).
11/15/14: Listed some miscellaneous items to order (XT60/XT90 connectors, microUSB
video breakout camera, etc), confirmed wiring of receiver to ESC/motor. Interfacing
controller to software proving much more difficult than originally expected.
11/23/14: Soldered connectors to battery and ESC’s, as well as all possible wiring (frame
not yet constructed). Calibrated ESC’s and confirmed function of each motor. Interfaced
manual controller to ESC’s. Divided and planned the end of semester report amongst the
group.
11/25/14: Determined the need for an adapter cable to live feed video to PC
(composite/s-video to USB connector (ADC)). Panicked some about impending due dates
for this report and the presentation - enough work is never done!
12/2/14: Received video breakout cable (microusb to base wires), attempted to get live
video feed, ran into regulated voltage problems which will be solved be making our own
switching regulators. Also noted the need to fabricate a custom 6 pin to 8 pin cable for
our telemetry and gps to link to our controller.
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Appendix B3: Safety Form
Hazard Category List specific hazards Shop or Lab to be Used
Name of individual providing training
Flammables (gas, oil, solvents, alcohol, kerosene)
Chemical hazards (acids, bases, toxic materials, paints, adhesives, epoxy, resin);
Epoxy, solder fumes Joe Zanetti (training already given)
Non-chemical Inhalation hazards (particulates/dust)
Biological materials (list type such as plant, cells, human subjects, etc.)
Physical hazards (heavy lifting, risk of crush injury; risk of slipping as a result of water or other liquids, etc)
Risk of injury if moving propellers are struck or if quadcopter free falls from the sky
Dean Schreiner & the group
Electrical hazards (use of high voltage >30V) equipment; electrical interface with the body such as electrodes
High current draw system (up to ~100 Amps), use of lithium polymer battery (highly flammable/explosive if not charged or discharged properly)
Dr. Adegbege
Non-Ionizing Radiation hazards ( lasers, near UV light; infrared, intense visible light; microwave, radio waves)
433MHz, 1.3GHz, 2.4GHz radio waves (all under one watt)
Dr. Katz
Ionizing radiation hazards (x-rays, radioactive sources that emit alpha, beta, gamma particles)
Use of compressed gases or cryogenic materials (liquid nitrogen, dry ice, etc)
Use of portable shop equipment (saws, drills, welder, etc.)
Use of drill press, soldering iron, hand tools
Machine Shop
Joe Zanetti (training already given)
Other Minor noise pollution from motors The group
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Appendix B4: Material List (derived from budget)
Frame and Flight Operation:
Power System:
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Communications:
Controller, Sensors, and Parachute
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Electrical Hardware and Tools:
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Appendix B5: Budget (color coded by vendor)
The actual given budget was $1,725.00, and did not include the +10% unexpected costs.
Should we run into anything that causes us to go over budget, Dean Schreiner requested
that we submit an allocation increase form at that time.
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Appendix C: Quadcopter dynamics state variables (Table C.1)
State Variable Definition
𝑝𝑛 North inertial position along 𝑖̂𝑖 in 𝐹𝑖
𝑝𝑒 East inertial position along 𝑗̂𝑖 in 𝐹𝑖
ℎ Altitude along −�̂�𝑖 in 𝐹𝑖
𝑢 Velocity of body frame along 𝑖̂𝑏 in 𝐹𝑏
𝑣 Velocity of body frame along 𝑗̂𝑏 in 𝐹𝑏
𝑤 Velocity of body frame along �̂�𝑏 in 𝐹𝑏
𝜙 Roll angle with respect to 𝐹𝑣2
𝜃 Pitch angle with respect to 𝐹𝑣1
𝛹 Yaw angle with respect to 𝐹𝑣
𝑝 Roll rate along 𝑖̂𝑏in 𝐹𝑏
𝑞 Pitch rate along 𝑗̂𝑏 in 𝐹𝑏
𝑟 Yaw rate along �̂�𝑏 in 𝐹𝑏