1 / 7

Intelligent Ground Vehicle Competition

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

rosa
Download Presentation

Intelligent Ground Vehicle Competition

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

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. EraldoRibeiro - 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. Overall Progress • Hardware • Not so good… hardware failures • Probably not ready for competition • Software Testing • Can’t test with a broken robot • Simulation alternative, difficult to simulate amount of data. • Will attempt anyway.

  4. Navigation Progress • Critical bugs squashed • Unit conversion • cm/s != mm/s • m/s != mm/s • When turning right, keep turning right? • “Random” equation coefficients shouldn’t be random. • Think function vastly more efficient • ~5 unnecessary loops eliminated

  5. Image Processing Progress • For line detecting, the camera works and detects every line. • Much faster than before. • Future • Integrate the VideoForm code to the main interface. • Minimizing the lines for white and yellow colors.

  6. Milestone 5 Task Matrix

  7. Questions, Comments, or Concerns?

More Related