Towards Establishing and Maintaining Autonomous Quadrotor Formations Audrow J. Nash William Lee College of Engineering University of North Carolina at Charlotte

Table of Contents 1.Introduction 2.Motivation 3.Research

What is a Quadrotor? Unmanned Aerial Vehicle (UAV) Four (quad) rotating propellers (rotor) Quadrotors have the ability to take off and land vertically

Quadrotor Applications 1.Carrying Payload 2.Surveillance

Why Swarm? We work together to accomplish more than we could alone

Quadrotor Swarm Applications 1.Carry Payload Moving objects Product delivery o Amazon o Africa o New York Build simple structures 2. Surveillance Disaster relief Building inspection Media Law enforcement Environmental And many more applications.

Current Research

More information University of Pennsylvania: ETH Zürich:

How does it work? 1.Infrared light reflects off quadrotors 2.Camera connected to computer analyzes 3.Instruction is wirelessly sent to quadrotor

Existing Research Decentralized control Brains are outsourced Unable to operate in real world environment.nationalgeographic.com / Current research has limitations for solving real world problems

Research Goal Develop an autonomous platform to have centralized control o Design quadrotor o Create and implement behavior algorithm

Quadrotor Platform

Flight system Purchased Handles stable flight with feedback from Inertial Measurement Unit All In One Pro V2.0

Quadrotor Platform

Wii Camera Extracted from Nintendo Wii controller Combined with infrared pass filter Tracks the four highest intensity infrared sources

Quadrotor Platform

Reference Beacon Composed of 4 infrared lights o Saturate camera capabilities B1, B2, B3 are for localization B4 reduces noise

Quadrotor Platform

Vision Processor Receives data from Wii camera Outputs movement command to flight system Red Board

Vision algorithm

Vision Code void loop() { if (IsLookingAtBeacon()) SendMovementCommand(); else Hover(); }

When Non Orthogonal Begins by flying to correct altitude Moves in front of beacon by comparing light source position

When Orthogonal

Characterizing Vision System Quadrotor distance from beacon (Inches) Amount of pixels between outer lights sources Data measured

Characterizing Vision System: Math Created and solved equations straight line approximations to determine quadrotor distance from reference beacon

Characterization Results

It was observed that the algorithm can direct a body to a position reliably with respect to the beacon void loop() { if (IsLookingAtBeacon()) SendMovementCommand(); else Hover(); }

Testing: Beacon Configuration Results: Use directional nature of lights Increased filtering

Testing: Environmental Lighting Impact Result: Indoor lighting conditions have no noticeable effect on vision system

Conclusion Benefits of full autonomy Created, implemented, and tested an autonomous system

Future Work Create autonomous test environment Achieve autonomous flight Implement swarm algorithm

Thank you! Audrow J. Nash University of North Carolina at Charlotte Charlotte, North Carolina