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Lunabotics Navigation Package

Lunabotics Navigation Package. Team May14-20 Advisor: Dr. Koray Celik Clients: ISU Lunabotics Club, Vermeer Company. Project Scope. NASA Lunabotics Mining Competition For university-level students to design and build a mining robot that can traverse the simulated Martian chaotic terrain

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Lunabotics Navigation Package

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  1. Lunabotics Navigation Package Team May14-20 Advisor: Dr. Koray Celik Clients: ISU Lunabotics Club, Vermeer Company

  2. Project Scope NASA Lunabotics Mining Competition • For university-level students to design and build a mining robot that can traverse the simulated Martian chaotic terrain • Points are awarded for autonomy • Landmarks allowed for navigation

  3. Project Scope Our Clients • Lunabotics Club • Vermeer Company • Large industrial and agricultural equipment

  4. Project Scope ISU Lunabotics Club • Bump detectors • Laser detector for orientation • No obstacle detection • LabView

  5. Project Scope Our Solution • Create prototype navigation system using computer vision techniques for navigation and object detection • Microsoft Kinect for prototype hardware solution • Open-source software

  6. Design Platform • Laptop Computer • 2.26 GHz Dual Core Processor • 4 GB RAM • Microsoft Kinect • RGB Camera • Infrared Optics • Robot ‘Virgil’

  7. Design Virgil • Built by Dr. Koray Celik • Representative of Lunabotics robot • Modified Kinect • Motor Controller • 4 Motors • Encoder Controller • 6 Encoders • Li-Ion Battery Powered

  8. Design Software • Ubuntu Linux 12.04 LTS • OpenCV 2.4.8 • OpenNI 1.5.7.10 • PropulsionClass

  9. Design

  10. Design

  11. Design Landmark Detection • Acquisition Module • Color Threshold • Canny Convolution Operator • Boundary Tracing • Rectilinear Object Recognition

  12. Landmark Detection Canny Threshold

  13. Landmark Detection Contour All Poly Filter

  14. Landmark Detection • Unobtrusive landmark, not likely to be found naturally • Searching for rectilinear shapes with overlapping midpoints • State-space reduction to reduce noise

  15. Design Obstacle Detection • Acquire depth map • Smoothing • Regression • Least Squares Plane Fitting

  16. Obstacle Detection • Plane Fitting • Least Squares Regression Normal Floor Plane Blue - Object Orange - Floor Smoothed Depth Mat

  17. Obstacle Detection • Threshold regression values • Contour Filter • Area of bounding rectangle

  18. Path Generation • Finite State Machine • Landmark must be in sight upon start • Drives towards landmark, avoids obstacles that appear in its path • Maintains spacial awareness to landmark in case it loses sight

  19. Path Gen • Find landmark • Move towards the landmark • Obstacle detected • Proceed on alternate path • Turn back to relocate landmark • Head to landmark

  20. Accomplishments Core Requirements • Robot Movement • Smooth Acceleration and turning • Position and heading • Landmark detection • Recognize and distinguish between our two landmarks • Obstacle detection • Recognise obstacles above 4 cm tall • Recognize Landmarks as not obstacles • Navigation • Obstacle avoidance

  21. Challenges • Landmark Detection • Noise reduction • Obstacle Detection • Uneven terrain issues • Encoder • Set back by hardware (group is more software oriented • OpenNI Bug • Appears around 3 minute mark • Prevents code from scalability in terms of computational complexity • Caused by XnSensorServer

  22. Testing Simulated Arena • 3 m X 2 m area • Virgil is representative of Lunabotics Club’s Robot Method • Test movement • Test landmark detection, eliminate false-positives • Test object detection • Test obstacle avoidance

  23. Demonstration https://www.youtube.com/watch?v=WRIJiebZkOs

  24. What’s Next? • Introduce Improved Hardware • 2.5-D Lidar • High Definition RGB Camera • Integrate Encoder Support • Improve Navigation Algorithm

  25. Questions?

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