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Maze Solving with an AIBO

Maze Solving with an AIBO. Bernard Maassen, Hans Kuipers, Max Waaijers & Andrew Koster 2005. Introduction. Problem: Maze Navigation Performed Research: Theseus found his way out of the Labyrinth Using IR for Maze Navigation, CMU www.cs.cmu.edu/~tekkotsu/media/pgss_2004_paper.pdf

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Maze Solving with an AIBO

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  1. Maze Solving with an AIBO Bernard Maassen, Hans Kuipers, Max Waaijers & Andrew Koster 2005

  2. Introduction • Problem: • Maze Navigation • Performed Research: • Theseus found his way out of the Labyrinth • Using IR for Maze Navigation, CMU • www.cs.cmu.edu/~tekkotsu/media/pgss_2004_paper.pdf • Many competitions • Many geometric algorithms for edge recognition and L-shapes • Computational Geometry: Algorithms and Applications

  3. Introduction • Why? • Many aspects, like: • Vision • World modeling • Self localization • Socially relevant: • Rescue robots need to navigate maze-like environments

  4. Problem Description • Maze Navigation • 3 Problems: • Landmark detection • Map construction • AIBO uses map to solve maze • Collision prevention/detection

  5. Landmark detection • Edge detection using scanlines • Only look below ‘horizon’

  6. Landmark detection • Possible Intersections

  7. Landmark detection • Possible Intersections

  8. Landmark detection • Possible Intersections

  9. Map construction • On each landmark update graph • Remember • Type of landmark • Current location • Use depth first search to explore • Initially simple mazes, later on more complex ones.

  10. Complications • Maze contains loops • Need to use distances as well as type of intersection • Different mazes • Curves • 5-way intersections • Other

  11. AIBO uses map to solve maze • Random initial location in maze • Use Bayesian filters to determine most likely location • Find exit

  12. Possible problems • Missing landmarks • Walking into walls • Odometry not reliable

  13. Backup plan • Reinforcement learning with joystick • Simpler • Uses joystick to train • Uses odometry data in stead of vision

  14. Milestone 1 • Joystick walking • Already in Tekkotsu • Integrate into DARPA modules • Collect odometry data

  15. Milestone 2a • Control point if 2b is feasible • If not extend Joystick module

  16. Milestone 2b • Landmark detection • Vision module • Edge detection + scanlines • Distinguish intersections

  17. Milestone 3 • Map construction • Model world as topological map • Self localization • Walking through the maze

  18. Milestone 4 • Maze Solving • Find place in world • Use map to find path to exit • Exit maze

  19. Milestones • Milestone 1: 30-9 • Milestone 2a: 19-10 • Milestone 2b: 26-10 • Milestone 3: 1-11 • Milestone 4: 11-11

  20. Vragen?

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