Mr. Fusion: A Navigation SolutionORAL PROPOSAL

DECEMBER 11, 2019

1

A NAVIGATION SOLUTION

OverviewProject Description

Guidance Subsystem

Navigation Subsystem

Control Subsystem

Hardware & Reliability

Power & Mechanical

Software Considerations

Cost & Marketing

Project Management

2

Guidance◦ David (Technical Lead)

◦ Sean

Navigation◦ Joseph (Project Lead)

◦ Emmett

Control◦ TJ

◦ Duncan

◦ Joy

◦ Connor

Team Layout

Project DescriptionJOSEPH KROEKER

3

Project OverviewAutonomous robot traversing campus◦ Autopilot subsystem to get to user-selected destination

◦ High-fidelity localization using sensor fusion◦ GPS + Inertial + visual & wheel odometry

◦ Real-time embedded processing on platform

4

(Sec 3.0, p.10)

Requirements & VerificationIADT Verification Methodology◦ Inspection

◦ Observation/measurement of a quality or quantity

◦ Ex. Size, weight

◦ Analysis◦ Mathematical backing without testing on real hardware

◦ Ex. MTTF, non-destructive performance degradation prediction

◦ Demonstration◦ Use normally and observe behavior

◦ Ex. UI interactions, timing

◦ Test◦ Intentionally force into boundary cases to tease out unlikely but required behavior

◦ Ex. Invalid user input, edge conditions

5

(Sec 4.0, p.19)

Requirements Summary

6

Number Requirement I A D T

4.1.2.3 The system shall operate for at least 1 hour without recharging.

X X

4.1.4.1 The system shall plan paths in areas that are traversable by the robot platform.

X

4.1.9.1.2 The robot platform shall have a ground clearance of at least 3 cm.

X

4.1.9.1.3 The robot platform shall handle a slope of at least 1:12 (ADA). X

4.1.9.1.4 The robot platform shall handle deviations from level plane including pavement cracks up to 2 cm in wide and 1 cm high.

X

(Sec 4.0, p.20)

Minimum Map BoundaryGreen circles are required UI locations

Red boundary includes required paths

(Sec 4.0, p.23)

7

Concept of OperationsRobot use case◦ Wireless UI for final

destination and cancellation

◦ Robot autopilot is a black box

(Sec 5.2, p.24)

8

System ComponentsAutopilot◦ All computation, functional behavior for guidance, navigation, and control (GNC)

User Interface◦ Wirelessly accessible for user input

Robot Platform◦ Motors + wheels, chassis for mounting electronics

◦ Off-the-shelf, 2-wheeled differential-drive + power supply

Sensor Suite◦ Hardware sensors, camera

9

GNC Subsystem DescriptionGuidance – What’s my path to destination?◦ Determines direction to next waypoint

Navigation – Where am I right now?◦ Estimates position, velocity, and attitude (PVA)

Control – How do I successfully move there?◦ Controller actuates motors to change PVA

10

(Sec 5.3, p.24)

Guidance SubsystemSEAN LINK

11

GuidanceHow does the robot get from its current location to user requested destination?

Subtasks◦ Reading a map of campus◦ Receiving input from a user◦ Determining the shortest path◦ Resolve discrepancies between the map and the actual

environment◦ Give instructions to the control system

12

Guidance

13

(Sec 5.5.1.1, p.51)

Campus Map

14

(Sec 5.5.1.1, p. 51)

Campus Map (cont.)<name>Line 4</name>

<LineString>

<coordinates>

-112.4494117,34.6162565,0

-112.449401,34.6161858,0

-112.4493996,34.6161582,0

-112.4493996,34.6161207,0

-112.4493996,34.6160777,0

-112.449401,34.6159839,0

-112.4494425,34.6158271,0

</coordinates>

</LineString>

15

(Sec 3.2.1.1, p.18)

User Input

16

Destination:

Student Union

(Sec 5.5.1.1, p.51-52)

Shortest Path

17

(Sec 3.2.1.1, p.17)

Graph vs Actual EnvironmentDependencies◦Knowing the robot's current location (requires integration to navigation)

◦Knowing a set of traversable paths (requires integration to the ToF camera)

18

Graph vs Actual Environment (cont.)

19

(Sec 5.5.1.1, p.51)

Graph vs Actual Environment (cont.)

20

Instructions to Control System

21

(Sec 5.5.1.1, p.51)

CPM Diagram for Guidance Sub-team

22

(Sec 6.1.1, p.72)

Guidance System - Current State

23

Navigation SubsystemEMMETT HAMMAN

24

NavigationCreate the best estimation of the robot’s current PVA.

Subtasks

•Define the Coordinate Frame for Navigation

•Overview of Sensors

•Methods for Sensor Fusion

•Implement Sensor Fusion

25

Coordinate FrameECI/ECEF vs. Tangential

26

(Sec. 3.2.2, p. 14)

Sensors

27

Package Sensor Measurement

Fixed Relative

STIM300 Gyroscope ω

Accelerometer a

VN-200 GPS r

Magnetometer ψ

Barometer h

Robot Motors Odometer v ω

AD-96 ToF Visual Odometer v ω

(Sec. 3.2.2, p. 15)

Sensor Fusion Methodology

28

(Sec. 5.3.2, p. 25)

Sensor Fusion Implementation

29

(Sec. 5.3.2, p. 27)

Schedule

30

Control SubsystemCONNOR ROCKWELL

31

ControlSend signals to motor encoders to produce a desired speed and heading from the robot◦ Control Theory

◦ Control Scheme

◦ Control sub-team timeline

32

Control TheoryOpen-loop System◦ Inputs translated to outputs

◦ Prone to instability

33

(Sec 3.2.3, p.16)

Control TheoryIndividual Wheel Closed-loop System◦ Includes feedback

◦ Single-Input-Single-Output

◦ Compares real value with desired value

34

(Sec 3.2.3, p.17)

Control SchemeRobot Control System◦ Multiple-Input-Multiple-Output◦ Input: Guidance info

◦ Controller: Control scheme for motors

◦ Feedback: Navigation info

35

(Sec 5.3.3, p.27)

Control SchemeHigh-Level Dynamic Model◦ Inputs:

◦ u1 – motor speed as voltage input for motor 1

◦ u2 – motor speed as voltage input for motor 2

◦ Outputs:

◦ v – speed of the robot

◦ θ – angle of orientation

36

Top-down view of robot

(Sec 5.3.3, p.28)

CPM Diagram for Control Sub-team

37

(Sec 6.1.3, p.60)

Hardware & ReliabilityTJ HALL

38

Hardware ConsiderationsComponent Selection

Processing

Sensing

Reliability

39

Component Selection Robotic Platform

◦ IG42-SB2, 2WD Tube Mount

Sensors◦ VN-200

◦ STIM-300

◦ ToF Development Kit

Processors◦ Raspberry Pi 4 (x2)

◦ Jetson

Other Hardware◦ Ethernet Switch

◦ NEMA Enclosure

40

(Sec 5.4.2.5, p.36)

Processing Guidance

◦ Raspberry Pi 4

◦ Path Planning

◦ UI

Navigation◦ Jetson Nano

◦ Sensor Data

Controls◦ Raspberry Pi 4

◦ Control Law

ToF Camera◦ DragonBoard 410c

◦ Image Flow

41

(Sec 5.4.1, p.32)

Sensing VN-200◦ GPS+IMU

◦ Magnetometer and barometer

STIM-300◦ IMU

◦ Accelerometer and gyroscope

IG42 Wheel Odometry◦ Encoders

AD-96TOF1-EBZ ToF Camera◦ Visual Odometry

◦ Traversability

42

(Sec 5.4.2, p.33)

Reliability MIL-HDBK 217F

Risks◦ Developmental

◦ Integration

Safety◦ Cutoff Switch

43

(Sec 5.7, p.61)

Power & MechanicalJOY FUCELLA

44

Power & Mechanical

45

Hardware Considerations

Power Board Design

Mechanical Concepts◦ Construction

◦ Mounting

Hardware Considerations

• Separate power supplies

• Battery life extended

46

(Sec 5.4.3, p.35)

Power Board Design

47

Component Iin_max Vin Pin_max

Raspberry Pi 4 3 A 5 V 15 W

Raspberry Pi 4 3 A 5 V 15 W

ToF Camera 4 A 5 V 20 W

Jetson Nano 4 A 5 V 20 W

DragonBoard 410c 3 A 6.5 V 19.5 W

Total 104.5 W

Battery Life: 2.2 hours

(Sec 5.4.4, p.36)

Power Board Design (continued)

48

(Sec 5.4.4, p.37)

Mechanical Concepts – Construction

49

• Two off-the-shelf robots

• Allows for concurrent testing

• Comes with instructions

• Printed Circuit Board (PCB) designed and constructed

• External protection purchased and modified

(Sec 5.6.1, p.55)

Mechanical Concepts – Mounting

50

• Structural support for the sensors

• Mount made from sheet metal

(Sec 5.6.2, p.55)

Software ConsiderationsDAVID STOCKHOUSE

51

Software ConsiderationsArchitecture

Data Flow

Control Flow

Implementation

Image Processing

52

(Sec 5.5, p.41)

Software ArchitectureGuidance

◦ Coarse and fine path planning, web server interface

Navigation◦ Kalman filter, hardware interfacing

Control◦ Control law, motor/encoder

interfacing

DragonBoard◦ ToF image processing for guidance

and navigation

53

(Sec 5.5.1, p.38)

Guidance Software Architecture

Path Planning◦ Reads external inputs

◦ Performs coarse and fine guidance

◦ Sends drive commands to control

54

(Sec 5.5.1.1, p.40)

Guidance Software ArchitectureUser Interface◦ Backend Server

◦ "Process" to service HTTP requests

◦ Direct interface between frontend and path planning

◦ Frontend Client◦ Executes on user's device

◦ Direct interface between user and autopilot

55

(Sec 5.5.1.1 p.40)

Navigation Software Architecture

Kalman Filter◦ Input measurements from all

sensors

◦ Output PVA estimate and uncertainty to guidance

Hardware Interface Threads◦ Serial buffers for

VN-200 and STIM300

56

(Sec 5.5.1.2 p.42)

Control Software Architecture

Control Law◦ Input speed and relative heading

from guidance

◦ Output necessary motor speed

Motor Interface Thread(s)◦ Serial interface for motor driver

and encoder buffer

57

(Sec 5.5.1.3 p.43)

Data FlowBetween processors◦ Ethernet PHY

◦ Interface protocol control next semester

Between processes◦ OS message queues

Between threads◦ Shared memory

58

(Sec 5.5.2, p.44)

Control Flow

59

Autonomous subsystems work as a pipeline

(Sec 5.5.3, p.45)

Control Flow GuidanceFSM

◦ Waiting after init

◦ Coarse guidance immediately after user input

◦ Active until reaches destination

60

(Sec 5.5.3, p.46)

Control Flow GuidanceRepeated primary loop

◦ Starts with time-step inputs

◦ Implements FSM behavior

◦ Ends with control output

61

(Sec 5.5.3.1, p.47)

Control Flow GuidanceSubroutines

62

(Sec 5.5.3.1, p.48)

Control Flow NavigationSimpler loop

◦ Read sensors

◦ Filter estimate

◦ Output estimate

◦ No FSM

63

(Sec 5.5.3.2, p.49)

Control Flow ControlMostly input/output

Forces keeping contact with guidance

64

(Sec 5.5.3.3, p.50)

ImplementationProof of Concept◦ MATLAB, Simulink

Embedded Software◦ C typical, Rust where appropriate

User Interface◦ Apache server hosted on guidance processor

◦ PHP backend

◦ Leaflet + JS frontend◦ Mapping GUI framework

65

(Sec 5.5.4, p.48)

Image Processing SoftwareGuidance◦ Traversability estimate

Navigation◦ Visual odometry

66

(Sec 3.2.4, p.18)

Sales, Cost, & MarketingDUNCAN PATEL

67

Sales, Cost, & MarketingSales Volume

NRE Costs

Recurring Costs

Sales Price

Return On Investment

Commercial Viability Horizon

68

Sales Volume

69

0

50

100

150

200

250

300

350

400

Vo

lum

e

Month of Sale

Sales Forecast

GROWTH

MATURITY

DECLINE

INTRODUCTION

(Sec 2.1, p.8)

Non-recurring Engineering Costs

70

Component Unit Cost Quantity Total Cost

Robot Platform * $1,500.00 2 $3,000.00

Raspberry Pi * $62.99 2 $125.98

Jetson Nano $99.99 1 $99.99

VN-200 $3,000 1 $3,000.00

STIM300 $10,000 1 $10,000

AD-96TOF1-EBZ $735.00 1 $735.00

NEMA Enclosure * $40.00 4 $160.00

Power Supply PCB * $40.00 3 $120.00

PCB SMD * $10.00 3 $30.00

Sheet Metal * $30.00 1 $30.00

Battery Enclosure * $7.68 3 $23.04

Ethernet Switch $16 1 $16

Total Cost $17,340.00

Actual Cost $3,505.01

Task Unit Cost Quantity Total Cost

Metal Bender $195.00 1 $195.00

Metal Drill Bits $149.99 1 $149.99

Power Drill $254.10 1 $254.10

Soldering Station $37.99 1 $637.08

Total Cost $637.08

(Sec 7.1, p.61)

Recurring Costs: Overhead & MarketingOverhead

◦ No hiring and firing throughout the project

◦ Even without tasks members can fill in where needed

◦ No overhead with project

Marketing◦ Pamphlet distribution across potential customers

◦ Pamphlets cost $25 each and printing for expected customers gives $3,750

◦ Online advertisements◦ Cost $1.25 per click with and expected $500 per month

◦ Initial cost of $4,250

◦ Monthly cost of $500

71(Sec 7.2, p.64)

(Sec 7.2, p.64)

Recurring Costs: Materials & Labor Component Unit Cost Quantity Total Cost

Robot Platform $1,500.00 1 $1,500.00

Raspberry Pi $62.99 2 $125.98

Jetson Nano $99.99 1 $99.99

VN-200 $3,000 1 $3,000.00

AD-96TOF1-EBZ $735.00 1 $735.00

NEMA Enclosure $40.00 4 $160.00

Power Supply

PCB

$40.00 3 $120.00

PCB SMD $10.00 3 $30.00

Sheet Metal $30.00 1 $30.00

Battery Enclosure $7.68 3 $23.04

Sensor Enclosure $6.38 4 $25.52

Sensor Power

Supply

$35 1 $35

Ethernet Switch $16 1 $16

Total Cost $5,900.53

72

Task Time (Hours)

Labor Count

Type Cost Per Unit

Soldering PCB 1 1 Assembly $95

Mechanical Mount Fabrication

1 2 Assembly $190

Robot Assembly 1 2 Assembly $190

Product Testing 1 1 Technician $125

Total $665

(Sec 7.2, p.64)

Sales PriceTotal Development Cost: $441,250

◦ Total Labor Development Cost: $404,000.

◦ Total Material Development Cost: $37,250

Total Volume Cost: $38,844,964.◦ Cost Per Unit: $6,466

◦ Material cost Per Unit: $5,800

◦ Direct Labor Cost: $665

Total Project Cost: $39,286,814

Adjusted Per Unit Cost:$6,539

Sales Price (5% profit margin):$6,865◦ Profit Per Unit Sold: $326

73

(Sec 2.2, p.9)

Return On Investment

-$900,000.00

-$800,000.00

-$700,000.00

-$600,000.00

-$500,000.00

-$400,000.00

-$300,000.00

-$200,000.00

-$100,000.00

$0.00

$100,000.00

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

ROI VALUATION CURVE

Per Unit Profit: $326

Monthly ROI: 9.34396%

Annual ROI: 192.104%

Max Calculated Debt: $6,540,962.72

Valuation: $0.71

74(Sec 7.3, p.65)

Commercial Viability Horizon

75

◦ ERAU, Prescott Campus Tour Guide◦ Cool Factor

◦ Assumptions

◦ Tour cost: 1 tour = $11

◦ Robot Use: 1 robot = 5 tours per week

◦ Estimations

◦ Robot Cost: 625 tours = 1 robot

◦ Cost Coverage: 2 years and 4 months = 1 robot

◦ Adaptability◦ New map must be loaded

(Sec 2.3, p.10)

Project ManagementJOSEPH KROEKER

76

Schedule – CPM Chart

77

(Sec 6.1, p.53)

Timeline

Prototype AssemblyJanuary 20, 2020

UI CompleteFebruary 7, 2020

Full System InterfacingMarch 23, 2020

Controls ImplementationFebruary 7, 2020

Guidance ImplementationFebruary 14, 2020

Subsystem InterfacingMarch 19, 2020

Full System TestingApril 20, 2020

Navigation ImplementationFebruary 24, 2020

End of DevelopmentMay 1, 2020

(Sec A.1, p.71)

Questions?David Stockhouse◦ stockhod@my.erau.edu

Joseph Kroeker◦ kroekerj@my.erau.edu

Joy Fucella◦ fucellaj@my.erau.edu

TJ Hall◦ hallt27@my.erau.edu

79

Emmett Hamman◦ hammane@my.erau.edu

Connor Rockwell◦ rockwec1@my.erau.edu

Sean Link◦ links3@my.erau.edu

Duncan Patel◦ pateld19@my.erau.edu

Backup Slides

80

Schedule – Gantt Chart

81

IMU Tangential Mechanization Equations

82

Kalman Filter Algorithm

83

Trade StudiesRobotic Platform

84

Trade StudiesSensors

85

Trade StudiesMotor Drivers

86

Battery Life Calculation(24 V / 104.5 W) * 9.6 Ahr = 2.2 hours

87

Sales Volume Table

88

Calendar

Month

Aug20 Sep20 Oct20 Nov20 Dec20 Jan21 Feb21 Mar21 Apr21 May21 Jun21 Jul21

Sales

Forecast

14 18 25 37 59 88 124 147 176 211 253 278

Calendar

Month

Aug21 Sep21 Oct21 Nov21 Dec21 Jan22 Feb22 Mar22 Apr22 May22 Jun22 Jul22

Sales

Forecast

305 335 341 347 353 360 342 324 307 276 248 223

Calendar

Month

Aug22 Sep22 Oct22 Nov22 Dec22

Sales

Forecast

200 180 162 145 130

ROI

89

Low-Level Plant Model for MotorP(s) – transfer function of the plant

V(s) – armature voltage

θ(s) – motor speed

J – moment of inertia

b – motor viscous friction constant

L – armature inductance

R – armature resistance

K – motor torque constant

90