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New Jersey Autonomous Vehicle. Brandon Schiff Jason Scott Jared Milburn. Abstract. Comprised of one mechanical and two computer engineers Construct vehicle to navigate through an obstacle course by GPS Waypoints Improving previous model Compete in the 22 nd Annual IGVC.
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New Jersey Autonomous Vehicle Brandon Schiff Jason Scott Jared Milburn
Abstract • Comprised of one mechanical and two computer engineers • Construct vehicle to navigate through an obstacle course by GPS Waypoints • Improving previous model • Compete in the 22ndAnnual IGVC
Table of Contents • IGVC • Frame Design • Electronics • Alogrithm Design • Future Plans • Budget
Intelligent Ground Vehicle Competition (IGVC) • The 22nd Annual Intelligent Ground Vehicle Competition • Oakland University in Rochester, Michigan • June 6 – June 9, 2014 • Ground Vehicle • Autonomous • Qualification • Basic and Advance Courses
IGVC Rules and Regulations • Size • Length – 3ft-7ft • Width – 2ft-4ft • Height – Under 6ft • Speed • Average – 1 mph • Minimum – 1 mph • Maximum – 10 mph • Propulsion • Emergency Stop • Wireless • Mechanical • Safety Light • Payload • 18” x 8” x 8” • 20 Pounds
IGVC Courses • Grass with Dashed Lines • Natural and Manmade Objects • Waypoints • Colored Flags • Fencing
Frame Design • Previous Frame • Stress Analysis • Compliance with IGVC Rules • Material Used
Analysis of previous team’s frame: Left and right: deformation caused by load and laser range finder
IGVC Spec. • Still the best design iteration • Functional design • Cons have simple solutions • Allows focus to be shifted to ensuring vehicle is fully operational • Blue Loctite used to lock bolts in place
Material 6105 T5 Aluminum Fractional T-slotted bars Product Number: 1010 Cross Sectional Dim.: 1.00” x 1.00” E = 10,000ksi ν = 0.33 • Reasoning: • Budget Friendly • Lightweight • Machinable • Modular
Electronics Overview • Allows the vehicle to be aware of it’s environment and location • Powered by two separate on-board batteries or laptop. • Laptop used for data processing of electrical components
Drive Train Diagram Manual E-Stop Button 12 Volt Battery Relay Wireless E-Stop Button Motor Controller Microcontroller Motor Motor Optical Encoder Optical Encoder
Drive Train Propulsion • Four Wheels, Two Wheel Drive • NPC-42150 Motors • DC Motors • Torque - 100 Psi • 93 Rpm • Previous Years • Motor Controller • Model – Sabertooth 2x25 V2 • Controls both motors • Controlled through serial ports • Previous Years
Feedback System • Measure Wheel Speed • Optical Encoder • Attached to gear shaped Disk • LED Light • Voltage Pulses Tooth No Tooth Voltage
Global Positioning System (GPS) • Used to navigate vehicle to given GPS location • Data sent via serial connection to Arduino port • Used in accordance with magnetometer
Digital Compass • Reads current vehicle orientation • Digital as opposed to analog compass • Accompanies GPS system • Arduino serial connection and power
Webcam • Used to feed real time images of the course to our laptop • Primarily focused on line detection as opposed to object detection • Filters out unnecessary visual information through applying masks and focuses only on discovering white lines • Recognition of white lines fed into path planning algorithm
Laser Range Finder • Short range laser used for object detection • Properties • Data sent via RS232-to-USB connection with laptop • Output
Power Systems • Laser Range Finder/GPS operating on two 12V batteries • Compass/Webcam/Warning Light/Motors and Motor Controller running on 12V • Sensors and vehicle operations communicates with Arduino Mega • Software-processing laptop sends and receives data with Arduino
Microcontroller • Arduino Mega • Outputs 3.3V and <50mA • Powered and communicates with laptop via USB • Arduino IDE
Caution Light GPS Microcontroller Laser Range Finder Compass RC and RC Controller Communication Hub Camera Motors Laser Range Finder Software Arduino Software D* Lite - Software - Hardware Components - Arduino - Laptop Camera Software C++ (Eclipse IDE)
Algorithm Design • Algorithms for the autonomous vehicle need to be robust and simple • Navigation and Path Planning algorithms are required for optimal performance • Navigation algorithm relies on utilizing the capabilities of the GPS and Compass while the Path Planning algorithm relies on the webcam and laser range finder
Navigation • Determines the vehicle’s current position, maintains a list of waypoints, and keeps track of the vehicle’s progress • GPS must accurately determine and report the vehicle’s latitude and longitude • Compass must give the vehicle’s current heading
Path Planning • Going to use D* Lite path planning • D* is an assumption based algorithm useful for when a robot needs to navigate to a given goal in unknown terrain • D* Lite works with the same functionality as D*, but it is simpler to understand and easier to execute
Software Used • Previously • Matlab • Microsoft Visual Studio • Open CSV • Arduino IDE • Now • Eclipse C++ Language IDE • AVR-GCC Compiler • AVRdude
Software Goals • Reproduce all MATLAB code in C++ • Testing of C++ code • Write path planning and navigation algorithms • Final program formulated using Microsoft Visual Studio and OpenCV
Future Plans • Frame covering • Full electrical system finalized, connected, and run simutaneously • RC controller configuration and testing • New coding, testing and debugging
NJAV Future Plans • Spring • Finalize Frame and Drive Train • Path Planning Components Working in Sequence • Debugging and Testing • Summer • Final Testing and Preparation for IGVC
Acknowledgements • Dr. Jennifer Wang • Advisor – Professor of Mechanical Engineering – The College of New Jersey • Dr. Orlando J. Hernandez • Advisor – Professor of Electrical and Computer Engineering – The College of New Jersey • Mr. Joseph Zanetti • Professional Services Specialist – School of Engineering – The College of New Jersey • Dr. Steven Schreiner • Dean of the School of Engineering – The College of New Jersey
Questions? • New Jersey Autonomous Vehicle • Jason Scott • Jared Milburn • Jonathan Sayre