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Towards Establishing and Maintaining Autonomous Quadrotor Formations Audrow J. Nash William Lee College of Engineering University of North Carolina at Charlotte Email: anash13@uncc.edu
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Table of Contents 1.Introduction 2.Motivation 3.Research
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What is a Quadrotor? Unmanned Aerial Vehicle (UAV) Four (quad) rotating propellers (rotor) Quadrotors have the ability to take off and land vertically
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Quadrotor Applications 1.Carrying Payload 2.Surveillance
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Why Swarm? We work together to accomplish more than we could alone http://otrazhenie.files.wordpress.com/2014/03/teamwork5.jpg
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http://vortex.accuweather.com/adc2004
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http://environment.nationalgeographic.com/
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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.
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Current Research http://defensetech.org/
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More information University of Pennsylvania: www.grasp.upenn.eduwww.grasp.upenn.edu ETH Zürich: www.idsc.ethz.ch/Research_DAndreawww.idsc.ethz.ch/Research_DAndrea
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How does it work? 1.Infrared light reflects off quadrotors 2.Camera connected to computer analyzes 3.Instruction is wirelessly sent to quadrotor http://images.gizmag.com/hero/nanoquadrotors-2.jpg
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Existing Research Decentralized control Brains are outsourced Unable to operate in real world http://vortex.accuweather.com/adc2004 http:// environment.nationalgeographic.com / Current research has limitations for solving real world problems
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Research Goal Develop an autonomous platform to have centralized control o Design quadrotor o Create and implement behavior algorithm
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Quadrotor Platform
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Flight system Purchased Handles stable flight with feedback from Inertial Measurement Unit http:// www.rctimer.com/index.php?gOo=goodspic.dwt&goodsid=765 All In One Pro V2.0
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Quadrotor Platform
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Wii Camera Extracted from Nintendo Wii controller Combined with infrared pass filter Tracks the four highest intensity infrared sources
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Quadrotor Platform
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Reference Beacon Composed of 4 infrared lights o Saturate camera capabilities B1, B2, B3 are for localization B4 reduces noise
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Quadrotor Platform
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Vision Processor Receives data from Wii camera Outputs movement command to flight system https://cdn.sparkfun.com//assets/parts/7/5/6/0/11575-01.jpg Red Board
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Vision algorithm
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Vision Code void loop() { if (IsLookingAtBeacon()) SendMovementCommand(); else Hover(); }
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When Non Orthogonal Begins by flying to correct altitude Moves in front of beacon by comparing light source position
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When Orthogonal
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Characterizing Vision System Quadrotor distance from beacon (Inches) Amount of pixels between outer lights sources Data measured
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Characterizing Vision System: Math Created and solved equations straight line approximations to determine quadrotor distance from reference beacon
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Characterization Results
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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(); }
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Testing: Beacon Configuration Results: Use directional nature of lights Increased filtering
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Testing: Environmental Lighting Impact Result: Indoor lighting conditions have no noticeable effect on vision system
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Conclusion Benefits of full autonomy Created, implemented, and tested an autonomous system
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Future Work Create autonomous test environment Achieve autonomous flight Implement swarm algorithm
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Thank you! Audrow J. Nash University of North Carolina at Charlotte Charlotte, North Carolina 28223 Email: anash13@uncc.edu
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