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The Bearcat Cub V

The Bearcat Cub V. Presented June 9, 2012 By William Hilton and Nicholas Vuotto. Outline. Our Team Introduction to the Cub Sensors Last year’s performance Design enhancements Wireless E-stop Wired E-stop Additional enhancements Lane Detection Obstacle Avoidance Conclusions.

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The Bearcat Cub V

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  1. The Bearcat Cub V Presented June 9, 2012 By William Hilton and Nicholas Vuotto

  2. Outline • Our Team • Introduction to the Cub • Sensors • Last year’s performance • Design enhancements • Wireless E-stop • Wired E-stop • Additional enhancements • Lane Detection • Obstacle Avoidance • Conclusions

  3. Our Team • University of Cincinnati • Participated all 20 years of IGVC • Currently all undergraduates 010000100101101010010010 010000100101101010010010 010100110100 010100110100 010000100101101010010010 010100110100

  4. Introduction to the Bearcat Cub • Incremental evolution of last year’s vehicle • Two deep cycle marine batteries for power • Segway wheels and gearboxes for motion • Sensors mounted on mast for intelligence • Dell laptop to control it all

  5. Sensors • SICK Lidar • Bumblebee stereovision • Two Sony camcorders • Novatel GPS • HMR Compass • Wheel encoders

  6. Last Year’s Performance • We qualified! • 1st run: software crashed • 2nd run: E-stop demonstration caused software crash & full reboot • Fuses in inverter blew preventing further attempts Lesson learned: more robustness!

  7. Wireless E-stop Remote Kill Switch with 2.5x factor of safety! 250 feet

  8. Wired E-stop New, schematically simpler system. Easier to reset & doesn’t crash code.

  9. Additions Since Report Since the written report was submitted, the following changes have been made: • Foam safety bumper • Upgraded safety light from parallel port to USB • Added 100A circuit breaker • And central fuse box • Code stability improvements

  10. Lane Detection • HSV thresholding for color detection • Hough transform to find best line fit

  11. Obstacle Detection • Uses LIDAR and stereovision • Obstacles create virtual repelling forces • Target creates virtual attractive force • Heading determined by summing the forces

  12. Conclusions • The same software algorithms as last year: • but better tested! • Upgrades to the electrical system and the frame to be: • More reliable • Safer • Competition, here we come!

  13. Thanks to • Our mentor, Professor Humpert • University of Cincinnati Center for Robotics Research • IGVC Committee Questions?

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