The CarBot Project
Group Members: Chikaod Anyikire, Odi Agenmonmen,
Robert Booth, Michael Smith, Reavis Somerville
ECE 4006 November 29th 2005
Presentation Outline
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Project Overview
Management Plan
Four core tasks
Cost Analysis
Market Analysis
Conclusion
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Project Overview
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Objective: To develop an autonomous vehicle that travels from
point A to B
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Features of an autonomous vehicle
 Detect and react to traffic lights
 Change lanes to maneuver around obstacles
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This project will pave the way for significant advancements in
transportation and provide a service that will revolutionize the
way people travel.
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Management Plan
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The management plan consisted of three phases.
Planning and Strategy
 Four Core Tasks
 Traffic Light
 Cmucam
 Robot Integration
 Robot Coding
 Final Testing
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Planning and Strategy
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Implement a small scale simulation of a
autonomous vehicle
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Preliminary Design Decisions
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What robot to use as a vehicle?
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Mekatronics Talrik II
What camera to use for detections?
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CMUcam v1.0 vs. CMUcam v2.0
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Traffic Light Implementation
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Determine the best traffic light solution (Bulb vs. LED)
COLOR
PRODUCED
POWER
CONSUMPTION
REQUIRED
VOLTAGE
LUMINOUS
INTENSITY
COST
LIGHT BULB
LED
White Light
20Watts/Bulb
True Color at
specified wavelength
1 Watts/LED
12 Volts
3-5 Volts
1700 mcd
6000 mcd
$1/BULB
2 cents/LED
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LED Versus Bulb (cont.)
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LED was the obvious winner in all facets of our requirements.
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Traffic Light Circuit
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CMUCam
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Track the position and size of a colorful or
bright object
Measure the RGB statistics of an image region
Automatically acquire and track the first object it
sees
On-board real-time vision processing
RS232 interface
RX – Receive
 TX - Transmit
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Camara Integration
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Motorola 68HC11
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Serial Peripheral Interface (SPI)
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Devices communicate using a master/slave relationship
Synchronous serial data link that operates in full duplex
MOSI – Master Out Slave In
MISO – Master In Slave Out
CLK – Clock
CMUcam is a SX28 microcontroller
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Interfaced with a OV6620 Omnivision CMOS camera
Serial Port
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Pin 2 – PC Receive/Scenix Transmit
Pin 3 – Scenix Receive/PC Transmit
Pin 5 – Ground
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CMUcam Implementation
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External Circuit Solution
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Max3100 to convert the SPI signals to rs232 signals
Oscillator to ensure that both the interfaces are operating at
the same frequency
Software Setup Solution
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C code needed for the microcontroller to communicate with
CMUcam
Sets up timing parameters (i.e. baud rate: 9600), etc.
Interprets the data from the camera to control robot
movement
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Robot Integration
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3 IR detectors
6 IR LEDS
ICC Programming
environment
SPI interfaces with
camera
Left/Right Motor
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Stay Straight Algorithm
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Design Problem: several
robot movement
problems
Solution: error algorithm
to prevent robot from
pulling left or right
Check Global
Left / Right
Get LA
LA = 5 point running
average
Get RA
RA = 5 point running
average
Compare to LP
(initial readings)
Compare to RP
(initial readings)
Convolution
Convolution
Send Results
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Change Lanes
Is Car in front?
YES
Check Opposite
Lane
CAR PRESENT
STOP
NO CAR PRESENT
Change Lanes
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Traffic Light Detection
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The cmucam will
constantly alternate being
tracking colors yellow,
red, and green.
Several cases that the
robot will encounter
Yellow
Red
Green
Action
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Go
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Stop
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Track Red / Green
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Stop
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Go
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Final Testing
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Creating a course to test the autonomous robot
Finalizing integration of camera and
microcontroller
Debugging problems in robot movement
algorithms
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Cost Analysis
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Estimated costs of car camera system 1/8 size
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Total non-recurring cost of $980,000
R&D will be the significant portion of initial costs estimated
to be $700,000
The return on this investment will be substantial when a
working model is produced.
The initial investment in this technology will be large
because the system has to be reliable, safe, and cost
effective.
This is an unique technology, and it is difficult to
estimate the initial market demand.
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Market Analysis
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This product has the potential to revolutionize the way
people travel
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Several cases where automated driving could prevent an
impaired driver from operating a vehicle
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This is a unique product, and being able to introduce it
into the automotive industry first will lead to huge
technological advantage over possible competitors, and
large revenue over time
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Real World Applications
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Pedestrian detection
Lane following
“Blind spot” detection
Parking aids
The Handicapped
Driver assistance – will be interchangeable with
the user
Military
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Questions
Are there any questions?
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