1 / 24

Skynet An Autonomous Quatrocopter

Skynet An Autonomous Quatrocopter. Designed by Andrew Malone And Bryan Absher. Introduction. Flying robot Self stabilizing Able to fly in preprogrammed patterns Autonomous Low cost. Outline. Block Diagram PWM Control Motor Driver Circuit Wireless Communications Sensors

lilah
Télécharger la présentation

Skynet An Autonomous Quatrocopter

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. SkynetAn Autonomous Quatrocopter Designed by Andrew Malone And Bryan Absher

  2. Introduction • Flying robot • Self stabilizing • Able to fly in preprogrammed patterns • Autonomous • Low cost

  3. Outline • Block Diagram • PWM Control • Motor Driver Circuit • Wireless Communications • Sensors • Control System • Results • Applications • Future Improvements

  4. Power Consumption • Logic Power • 2 x PICLF877A Microprocessor • 0.6mA at 3 V and 4Mhz • 3 x LY530ALH 1 Axis Gryroscope • 5mA at 3 V • ADXL335 3 axis Accelerometer • 3 uA at 3 V • Use 2 button batteries at 150mAh each

  5. Motor Driving System • Control of High-Current Motors with a Microprocessor • Microprocessor Output • PIC16F877A • 2V to 5V max ~25mA • Motor • GWS EDF50 • ~4 Amps at 10.8 V

  6. PWM Characteristics • Output Voltage is Simulated • Device is Switched On and Off • PIC PWM max 25mA • Magnifies Motor Driving Concerns • Inductance • Generation • Noise • Power on Ground

  7. System Requirements • Extremely High Current Gain • ~1000A/A • 10V Maximum Output from 11V Supply • High Current Output • ~5A per Motor • Fast Switching Time • < 20µs • Complete Electrical Isolation • No Common Ground

  8. Optical Isolation • Anode and Cathode Voltages drive infrared LED • Light Modulates Phototransistor Base Voltage • Complete electric isolation • Cheap ($0.60 EE store) • Fast (5 – 10 µs) • TIL111 • Perfect for PWM

  9. Darlington Transistor TIP 122 • 5A Max Current • β >1000 at 5A • ~1V VCE • < 20µs Switching Time

  10. Delivery to Motor • AC Output Interacts with Inductance • Motors Prefer DC inputs • Low-pass Filter http://www.zen22142.zen.co.uk/Design/dcpsu.htm

  11. Final Circuit Design

  12. Wireless Communication • IEEE 802.15.1 (Bluetooth) • Low power (100mA Tx, 20mA Rx) • Complex Protocol Stack • Small Network Size • Fast Data Rates (1.5 Mbit/s, or 3 Mbit/s) • IEEE 802.15.4 Zigbee • Low power • Low overhead • Slower data rates • Large network size

  13. Our Implementation • Simple configuration • UART communications • 115 kBaud (Limited by PIC16LF877A) • 3.3 V • RN-41-SM • Light weight • Low power • High data speed • Good for tuning PID

  14. Sensor Theory • Accelerometer • Charged cantilever • Change in acceleration changes the capacitance of the cantilever

  15. Sensor Theory • Gyroscopes • MEMS gyroscopes consist of a vibrating structure • Angular velocity changes the vibration

  16. Sensor Implementation • Ideal implementation: • Initial angles = arctan(x/z) and arctan(y/z) • ω from gyroscope reading • Subsequent angles = initial angles + ∫ω*dt • Accelerations relative to ground derived from accelerometer combined with gyroscope angle readings • Velocity = ∫a*dt • Position = ∫v*dt

  17. Sensor Implementation • Accelerometers and Gyroscopes vary widely from specification • Accelerometer bias must be calibrated • Gyroscope bias varies over time • Inaccurate over long periods • Readings can be corroborated using a Kalman Filter • Integrals rely on fast sampling rate

  18. Sensor Implementation Angle • Assume gravity is greatest acceleration • Angle = arctan(r/z) • Extremely accurate • Change in Altitude • Integrate Z-axis acceleration • Accurate for very small accelerations

  19. System Control • PID control • Proven method • Standard Tuning methods • Ziegler–Nichols • Effective at controlling high order systems

  20. Our Control System

  21. Results • PID-controlled power output • Accurate angular orientation measurement • Sufficient lift, battery life • Wireless feedback

  22. Applications • Aerial Displays • MIT Flyfire • Flying sensor network • Autonomous surveillance

  23. Improvements • 32 or 16bit ARM processor at 100 Mhz • Horizontal motion measurements • Local or Global GPS • SONAR • Environment sensors • CO2 • Visual • Wind Speed • ZigBee mesh network • Create a flying sensor network • Distributed intelligence • Kalman Filter • Reduce noise in angle measurements

More Related