1. LUNAR Lunar Unmanned Navigation and Acquisition Robot SECON I Senior Design I Final Design Review November 29, 2007

2. Team 1 Dr. Bryan Jones, Advisor Ted Copeland Bryan Reese Theresa Weisenberger Jeffrey Lorens Block DetectionXX Path DetectionXX Object AvoidanceXX CommunicationXX

3. Outline Competition Overview Practical Constraints Technical Constraints Models Testing Spring Semester Goals

4. Competition: Summary Lunar mineral harvesting robot Color-coded blocks with RFID tags Collect maximum of four blocks and bring them back to home base Final rounds head-to- head

5. Competition: Court Home Bases Red/Blue/White Blocks X Black Blocks Pea Gravel Sand Paint 6 ft Symmetrical Block Placement IR Beacons (2.5kHz and 4 kHz) on Home Bases Note: Grid will not be on the field during competition X

6. Competition: Approach

7. Outline Competition Overview Practical Constraints Manufacturability Sustainability Technical Constraints Testing Spring Semester Goals

8. Practical Constraints TypeNameDescription ManufacturabilityModularity The robot must be designed as a set of subsystems that can be replaced independent of other subsystems. SustainabilityDependability The robot must be sturdy enough to withstand repeated use.

9. Modularity Team One Block Detection Path Planning Object Avoidance Home Base Detection Team Two Locomotion Block Retrieval Block Storage

10. Modularity-Team 1 Subsystems Environmental Sensing IR Distance Sensors Limit Switches Vision Block Detection IR Sensor CMUCam3

11. Sustainability Robot must be able to run full round (6 min) without repair. Rugged enough to sustain normal wear. Only minor maintenance between rounds. Easily changeable battery

12. Sustainability Battery Life: 5 rounds on 1 charge Performs consistently after multiple tests Normally no maintenance between rounds Battery slips into sleeve

13. Outline Competition Overview Practical Constraints Technical Constraints Models Testing Spring Semester Goals

14. Technical Constraints NameDescription Block Detection The robot must be able to detect and distinguish among red, blue, black, and white blocks. Path Planning The robot must find a path to a target block while avoiding any obstacles.

15. Block Detection IR distance sensor Requests color identification from camera Color Differentiation Prioritize block pick up Minimize the time spent collecting blocks

16. Path Planning Center Line Detection Black block Reference point Block Location Home Base Detection

17. Outline Competition Overview Practical Constraints Technical Constraints Models Testing Spring Semester Goals

18. Physical Model Camera Block Detection Sensor Environmental Distance Sensors Collision Detection Sensors

19. Physical Model Environmental Distance Sensors Block Detection Sensor Collision Detection Sensors

20. Wall Detection IR Distance Sensors Limit Switches (4) Environmental Sensing Subsystem Vision Subsystem Distance to wall CMUCam3 RS-232 bidirectional serial SPI bidirectional serial Block Detecting IR Distance Sensors Block Present Block Color PIC18F4420 Microcontroller Block Collected Team 2 Microcontroller Drive Commands Front Information Model Back Right Side Left Side

21. Outline Competition Overview Practical Constraints Technical Constraints Models Testing Spring Semester Goals

22. Testing-Block Detection Camera returns mean color value of block PIC determines block color Tested at each of three possible locations Subsystems Tested CMUCam3 RS-232 Serial Communication

23. Block Detection Results Color Identified by Vision Subsystem Block ColorLocation ALocation BLocation C Blue White Red

24. Testing-Path Planning Robot starts at home base Measures center-line detection accuracy Subsystems Tested IR Distance Sensors SPI Communication Analog-to-Digital Converter x x x x x

25. Results-Path Planning Trial Distance from Center (inches) Percent Error 100% 20.6251.74% 312.78% 40.250.69% 50.51.39%

26. Outline Competition Overview Practical Constraints Technical Constraints Models Testing Spring Semester Goals

27. More precise environmental sensing Camera integration Enhanced object avoidance system Playoff round capability

28. References Huntsville IEEE Section. "SoutheastCon 2008 Hardware Competition Rules: Return to the Moon," IEEE SoutheastCon 2008. 2007. Available: http://ewh.ieee.org/reg/3/secon/08/competition. html http://ewh.ieee.org/reg/3/secon/08/competition. html Questions?