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Capstone Design Project Plan. Ryan Campbell. Anne Carrier. Team SAUSAGES. Gonzalo Gonzalez. Bryan Grider. Steve Kerkmaz. EE 401 – EE Design I Instructor – Dr. Mohan April 13, 2003. Ziad Mohieddin. IGVC Standards 0 to 8 kph speed range 2 to 5 m radius turns 3 m following distance
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Capstone Design Project Plan Ryan Campbell Anne Carrier Team SAUSAGES Gonzalo Gonzalez Bryan Grider Steve Kerkmaz EE 401 – EE Design I Instructor – Dr. Mohan April 13, 2003 Ziad Mohieddin
IGVC Standards 0 to 8 kph speed range 2 to 5 m radius turns 3 m following distance No modification to Lead Vehicle Course Obstacles UDM Standards 0 to 8 kph speed range 2 to 5 m radius turns 1 m following distance Allowed to mount targets and sensors on Lead Vehicle Obstacle Free Problem Statement and Project Objectives
Solution Strategy Chassis Computational Hardware Software Sensors Platooning Strategy
Solution Strategy Chassis Computational Hardware Software Sensors Platooning Strategy
Power Wheels Eliminator • Advantages • Pre-Built Systems • Large Available Area • Easily Modifiable • Inexpensive • Disadvantages • Traction • Steering Control
Chassis Modifications • Traction Control • Mount Conveyor Belt to Area of Contact with Ground • Steering System • Gear and Chain System • Servo or Window Motor
Solution Strategy Chassis Computational Hardware Software Sensors Platooning Strategy
Shuttle Barebone • Inexpensive • Interchangeable parts • Small package • 2 GB Maximum memory capacity
I/O Card • Counter/Timers • Used to create PWM signals • Digital Lines • Used for Ultrasound • A/D converters • Possibly used for backup sensors
Solution Strategy Chassis Computational Hardware Software Sensors Platooning Strategy
Donated by BOSCH Once in diagnostic mode, outputs 1 byte every 25 ms 1 bit = 1 cm of distance Ultrasound Sensors
CMUcam OVERVIEW • SX28 Microcontroller interfaced with a OV6620 omnivision CMOS camera. • $ 109.00
CMUcam Vision Sensor MAIN FEATURES AND FUNCTIONALITIES • 80 * 143 image Resolution. • Dump images (color blobs). • Track images at 17 frames / seconds. • Find centroid of image. • Adjust the camera’s image properties. • Ability to control a servo or use one Digital I/O pin. • RS-232 serial or TTL data communication.
CMUcam Vision Sensor DISADVANTAGES • Response to ambient and florescent light. • Servo’s sensitivity to image tracking.
CMUcam Vision Sensor RELEVANCE TO OUR PROJECT • Eyes for vehicle navigation. • Preliminary steps for steering control.
How does it work? • The black and white disk is for creating pulses. • The reflected beam on the black segment will cause the sensor to output a signal (pulse). • Each pulse corresponds to a specific distance traveled. • The number of pulses in a given time will determine the speed.
Speed • Number of pulses = (n) • Distance = (n * x) • Speed = Dist. / Time.
Solution Strategy Chassis Computational Hardware Software Sensors Platooning Strategy
Matlab/Simulink • xPC Target • Real-Time Workshop • Stateflow Coder
HOST PC (desktop) • Development of the • algorithm • Non-real time testing • of the algorithm • Tuning of the algorithm • using real-time signals • coming from the Target • PC • TARGET PC (on vehicle) • Real-time simulation of • the algorithm • Runs the final algorithm • on vehicle • On board implementation of the algorithm xPC Target
Stateflow Coder • Designs complex control systems based on finite state machine theory. • Represents the system logically and can eliminate the unnecessary states within the system. • The basic structure of the flow diagrams is created in Stateflow by complex if…then statements which allow the program to jump between two different algorithms .
Solution Strategy Chassis Computational Hardware Software Sensors Platooning Strategy
Platooning Strategy • The Platooning Strategy must use our sensors to allow us to follow our project constraints. • Our algorithm was developed using two algorithms.
