1. Bianca Wood Chris Culver Shane Parker Yousef Al-Khalaf

2. Motivation Challenge Our Capabilities Sense of Accomplishment Sheer Fun

3. Objectives Build a flying stable quadrotor Agile Real-time, intelligent decision-making Autonomous

4. Challenges Waiting for parts to come in Not having a proper testing environment (worked in a ditch literally) Making something fly, and also be stable Having our frame break two days before our final presentation

5. Specifications Each quadrotor is.91 m diamter Height of.178 m Weight ~ 5 lbs Able to operate for 15 minutes on a single charge

6. A.I. Controller Power System Image Processor Flight Control Current Position Shut Off Memory Power Switch Starting Pos. Motor Controller Camera Block Diagram Fire Control

7. A.I. Controller Power System Image Processor Flight Control Current Position Shut Off Memory Power Switch Starting Pos. Motor Controller Camera Block Diagram Fire Control

8. A.I. Controller Power System Image Processor Flight Control Current Position Shut Off Memory Power Switch Starting Pos. Motor Controller Camera Block Diagram Fire Control

9. A.I. Controller Power System Image Processor Flight Control Current Position Shut Off Memory Power Switch Starting Pos. Motor Controller Camera Block Diagram Fire Control

10. A.I. Controller Power System Image Processor Flight Control Current Position Shut Off Memory Power Switch Starting Pos. Motor Controller Camera Block Diagram Fire Control

11. Power Micro Controller Motor Movement A.I. Controller Flight Control Sub-System

12. Navigation Control Algorithm Coordinates / Sensors Motors Navigation Coordinates come from AI computer Stabilization Readings come from sensors PWM Signal

13. Rxacc = (ADCRx*Vref/1023 – Vzerog)/ Sensitivity Ryacc = (ADCRy*Vref/1023 – Vzerog)/ Sensitivity Rzacc = (ADCRz*Vref/1023 – Vzerog)/ Sensitivity R 2 = Rxacc + Ryacc + Rzacc 222 -ADC = Value coming from accelerometer -Vref = Reference voltage from ADC -1023 = Max value of ADC bus -Vzerog = Acc under 0 g’s of force -Sensitivity = Relationship between changes in acceleration to change in output Accelerometer ( ) Θxr = cos Rx R ( ) Θzr = cos Rz R ( ) Θyr = cos Ry R

14. Gyroscope θxy = Rotation around Z axis Yaw θyz = Rotation around X axis Roll θxz = Rotation around Y axis Pitch Rate θxy = (ADCxy*Vref/1023 – VoltsZeroRate)/Sensitivity Rate θxz = (ADCxz*Vref/1023 – VoltsZeroRate)/Sensitivity Rate θyz = (ADCyz*Vref/1023 – VoltsZeroRate)/Sensitivity -ADC = Value coming from gyro -Vref = Reference voltage from ADC -1023 = Max value of ADC bus -VoltsZeroRate = Output voltage when no rotation -Sensitivity = Change in output voltage with one degree per sec rotation

15. Combining Accelerometer and Gyroscope Data Takes Accelerometer data Checks it against Gyroscope data and past output data Corrects itself Rout(n) = Current output of Algorithm Rout(n-1) = Last output of Algorithm Rate θ = Gyro output Rgyro = Current gyro & past output combined

16. Θxz(n-1) = atan2(Rxout(n-1), Rzout(n-1)) Θyz(n-1) = atan2(Ryout(n-1), Rzout(n-1)) Θxy(n-1) = atan2(Rxout(n-1), Ryout(n-1)) Θxz(n) = Θxz(n-1) + Rate θxz(n)*T Θyz(n) = Θyz(n-1) + Rate θyz(n)*T Θxy(n) = Θxy(n-1) + Rate θxy(n)*T Rxgyro(n) = sin(Θxz(n)) / SQRT{1 + cos (Θxz(n) )*tan (Θyz(n))} 2 2 Rygyro(n) = sin(Θyz(n)) / SQRT{1 + cos (Θyz(n) )*tan (Θxz(n))} 2 2 Rzgyro(n) = SQRT( 1 – Rxgyro (n) – Rygyro (n)) 2 2 (T= sampling period) Rout(n) = Current output of Algorithm Rout(n-1) = Last output of Algorithm Rate θ = Gyro output Rgyro = Current gyro & past output combined

17. Rout(n) = Racc + Rgyro ( ) w2 w1 ( ) w2 w1 1 + ( ) w2 w1 * = How much to trust the gyro over the accelerometer

18. Computer Vision Haar Wavelets, first real time face detector. Viola and Jones adapted idea, developed Haar-Like- Features. Considers adjacent rectangular regions at a specific location in a detection window. Sums pixel intensities. Calculates difference between the sums.

19. Computer Vision Integral Image Algorithm Single Pass Over the Image Evaluating any Rectangle in Constant Time

20. Overall Software Class Diagram

21. Artificial Intelligence Subsystem

22. State Machine

23. Navigation Mesh

24. Path With Navigation Mesh

25. Hardware i7 Ivy Bridge 16GB DDR3 1600 with 9-9-9-24 Timings 120GB SSD NVIDIA 8900 GT

26. Voltage : 2.1 – 3.6 Frequency : 2.4 GHz Data Rate : 250 Kbps Range : 200 ft open space Voltage : 5 v Current : 500 mA

27. Power (2) Lithium-ion Polymer batteries 11.1 v 2200mAh Mounted on the bottom Camera powered by 9V PCB to disperse the power

28. Power Distribution Battery 1 Battery 2 PCB & Voltage Regulator ESC/Motor

29. PCB Power in from left and right Voltage regulator came with MCU 5V Regulator Receiving ~ 22V 2 diodes 4 arms to the ESCs/motors

30. PCB Power in from left and right Voltage regulator came with MCU 5V Regulator Receiving ~ 22V 2 diodes 4 arms to the ESCs/motors

31. PCB Power in from left and right Voltage regulator came with MCU 5V Regulator Receiving ~ 22V 2 diodes 4 arms to the ESCs/motors

32. PCB Power in from left and right Voltage regulator came with MCU 5V Regulator Receiving ~ 22V 2 diodes 4 arms to the ESCs/motors

33. Finances Motors (2) $500 donations PCB materials donated Self funded

34. Budget ItemQuantity Price per QuantityTotal Price Quadcopter Frames2$30, $100$130 Computer1$1,000($1,000) Motors12$10($120) Slowfly electric prop 1045R 4-piece set4$3$12 Wireless Microprocessor1$150 Wireless 2.4 GHz camera1$20 Wireless 2.4 GHz USB receiver1$40 Zigbee1$80 ESCs4$7$28 11.1V 2200mAh 25C LiPo Battery2$15$30 PCB1-- MiscellaneousUnknown Allocating $150 Total $640

35. Thank you Sponsors Jeff Moler Tim Parker John Enander Dr. Samuel Richie

36. Questions

37. Bianca Wood Chris Culver Shane Parker Yousef Al-Khalaf