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New Jersey Autonomous Vehicle

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  1. New Jersey Autonomous Vehicle Brandon Schiff Jason Scott Jared Milburn

  2. 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

  3. Table of Contents • IGVC • Frame Design • Electronics • Alogrithm Design • Future Plans • Budget

  4. 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

  5. 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


  6. IGVC Courses • Grass with Dashed Lines • Natural and Manmade Objects • Waypoints • Colored Flags • Fencing

  7. IGVC Courses

  8. Frame Design • Previous Frame • Stress Analysis • Compliance with IGVC Rules • Material Used

  9. Analysis of previous team’s frame: Left and right: deformation caused by load and laser range finder

  10. 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

  11. 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

  12. 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

  13. Drive Train Diagram Manual E-Stop Button 12 Volt Battery Relay Wireless E-Stop Button Motor Controller Microcontroller Motor Motor Optical Encoder Optical Encoder

  14. 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

  15. Feedback System • Measure Wheel Speed • Optical Encoder • Attached to gear shaped Disk • LED Light • Voltage Pulses Tooth No Tooth Voltage

  16. 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

  17. Digital Compass • Reads current vehicle orientation • Digital as opposed to analog compass • Accompanies GPS system • Arduino serial connection and power

  18. 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

  19. Laser Range Finder • Short range laser used for object detection • Properties • Data sent via RS232-to-USB connection with laptop • Output

  20. 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

  21. Microcontroller • Arduino Mega • Outputs 3.3V and <50mA • Powered and communicates with laptop via USB • Arduino IDE

  22. 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)

  23. 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

  24. 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

  25. 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

  26. Path Planning

  27. Software Used • Previously • Matlab • Microsoft Visual Studio • Open CSV • Arduino IDE • Now • Eclipse C++ Language IDE • AVR-GCC Compiler • AVRdude

  28. 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

  29. Future Plans • Frame covering • Full electrical system finalized, connected, and run simutaneously • RC controller configuration and testing • New coding, testing and debugging

  30. 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

  31. Budget

  32. 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

  33. Questions? • New Jersey Autonomous Vehicle • Jason Scott • Jared Milburn • Jonathan Sayre