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Intelligent Ground Vehicle Competition Navigation Michael Lebson - James McLane - Image Processing Hamad Al Salem.

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Presentation on theme: "Intelligent Ground Vehicle Competition Navigation Michael Lebson - James McLane - Image Processing Hamad Al Salem."— Presentation transcript:

1 Intelligent Ground Vehicle Competition Navigation Michael Lebson - mlebson@my.fit.edu James McLane - jmclane@my.fit.edu Image Processing Hamad Al Salem - halsalem@my.fit.edu Shane Brumbley - sbrumble@my.fit.edu Faculty Sponsor Dr. Eraldo Ribeiro - eribeiro@fit.edu Project Website http://my.fit.edu/~mlebson/seniorDesign

2 Introduction Designing Control Software for autonomous obstacle course navigating vehicle. –Must navigate from waypoint to waypoint –Must use LIDAR, GPS, Digital Compass, and Camera to determine movement around the course –Must stay within lane lines and avoid obstacles in the completion lane

3 Refactoring Cleaning up existing code –Code Commenting Use external documentation –Code style Hungarian notation Standardized formatting –Organization Dividing large generic classes Ensure standards follow on new code Easy to refactor again in the future, if needed

4 Navigation Algorithm Enhanced Vector Polar Histogram (VPH+) Accounts for error in hardware readings/devices Groups obstacles into blocks to predict future obstacles Speed of robot and heading deviation Tested against normal VPH

5

6 Initial Image Processing Video class Making the camera capture video imagesMaking the camera capture video images Using the associated Webcam on the laptopUsing the associated Webcam on the laptop Fixing some exceptions and errors Fixing some exceptions and errorsNullReferenceException Error while updating the captured image VideoForm GUI Modifying some buttons to work as expectedModifying some buttons to work as expected Improve the interface for the Video windowImprove the interface for the Video window

7 Camera JVC GZ-HM320 camcorder Has HD 1920 X 1080 recording Streams directly to the computer Image Stabilization Is under budget compared to cameras with similar features

8 Image Processing Algorithm Image Processing Algorithm The image will be broken into a series of smaller grids –Each grid will be assigned a stable distance from the robot –Each grid will generate a number according to the color The numbers for white and yellow will raise a false flag, which tells navigation that the boundary occurred in the grid

9 Milestone 3 Task Matrix

10 Questions, Comments, or Concerns?


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