Establishing and Maintaining Formations of Mini Quadrotors Audrow J. Nash, Cory M. Engel, James M. Conrad William Lee College of Engineering University of North Carolina at Charlotte Charlotte, North Carolina

Abstract: What? Quadrotor system design – On-board processing Flight algorithm for motion planning – Can be expanded for swarms Start of solo quadrotor autonomous flight

Abstract: Why? Develop a base for swarm application, which has the following benefits: – Payload manipulation – Surveillance application – Search-and-Rescue

Abstract: Novel Contribution On-board processing (no external localization system) Use of Wii Camera for localization and motion planning

Table of contents 1.System Overview 2.Motion Planning Algorithm 3.Characterizing Vision System 4.Vision System Testing 5.Autonomous Flight Progress 6.Conclusion and Future Work 7.Contact Information

Overview: System Flow Chart

Overview: Wii Camera Monochrome 1024x768 camera – After initial resolution of 128x96 undergoes 8x subpixel analysis Tracks the four highest intensity light sources Outputs light source Cartesian coordinate (X, Y) and observed size Combined with infrared (IR) pass filter (extracted from Wiimote)

Overview: System Flow Chart

Overview: Reference Beacon Composed of 4 IR LEDs B1, B2, B3 for localization * Discussed later B4 to saturate camera capabilities – Reduce environmental noise

Overview: System Flow Chart

Overview: Vision Processor Receives Wii camera Data – Uses I2C Outputs movement command to flight system – PWM to mimic remote transmitter

Overview: System Flow Chart

Overview: Flight System Interprets movement commands from vision system and actuates accordingly Handles stable flight with input from sensors

Overview: System Flow Chart

System Overview: Sensors SensorPurpose Inertial Measurement Unit (IMU) Level/stable flight Sonar sensorMeasure altitude Wii Camera is not mentioned because it does not pass information to the flight system directly *

Overview: System Flow Chart

System Overview: Actuators

Motion Planning Algorithm: Overview

Motion Planning Algorithm: Code //Main loop void loop() { GetAverageBlobXYCoordinates(); if (IsLogical()) SendMovementCommand(); } Flight system will hover quadrotor until given a movement command to actuate *

Motion Planning Algorithm: NonOrthagonal Case Begins by flying to correct altitude – Beacon is half of possible Y value Alternates between adjusting yaw and roll (lateral movement) – Allows for constant site of beacon

Motion Planning Algorithm: Orthagonal Case Behavior begins when dobser:B1;B2 == dobser:B2;B3 Distance of the quadrotor from the beacon is proportional to the perceived distance between the first (B1)and third (B3)light source

Characterizing Vision System: Data Quadrotor distance from beacon Distance between outer light sources

Characterizing Vision System: Results Used equations to develop straight line approximations to determine quadrotor distance from reference beacon

Characterizing Vision System: Testing It was observed that the algorithm can direct a body to a position reliably with respect to the beacon for roll, pitch, and yaw

Vision System Testing: Beacon Configuration Results: Greater than 4 light sources is unreliable Additional check of beacon is necessary Mitigation: Increased filtering Directional nature of LEDs

Vision System Testing: Environmental Lighting Impact Results: Indoor lighting conditions have no noticeable effect on vision system Additional testing for outdoor conditions recommended

Autonomous Flight Progress Wireless call flight modes – Safe Mode: toggle to arm and disarm quadrotor – Stabilize: quadrotor flight remains level – Altitude hold: hover a specific height Vision system mimics transmitter signal to Flight system Role and pitch response to beacon

Conclusion Accomplished: – Quadrotor system – Algorithm for autonomous flight of a single quadrotor with on-board processing – Tested algorithm – Made progress towards autonomous flight

Future work Reliable autonomous liftoff/landing Increased logical checks of beacon Develop and test a swarm algorithm

Contact Info Audrow J. Nash, Cory M. Engel, James M. Conrad William Lee College of Engineering University of North Carolina at Charlotte Charlotte, North Carolina

Processor Specifications Vision SystemFlight System BoardRed BoardAll In One Pro V2.0 ProcessorATMega 328ATMega 2560 Flash32kB256kB Clock speed16MHz GPIO/Analog Inputs14/686/16 Other6 axis gyro/accel