Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Sophia Beckwith, Junior Carys Del Prete
Lead Presenter's Name
Sophia Beckwith
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Dr. Ronald Adams
Abstract
This project explores how imitations observed in animal group behavior, specifically flocking in birds, can be applied to the functionality of autonomous drone systems to aid in search and rescue efforts. The goal is to demonstrate how incorporating code based on the Boids, Vicsck and predictive control linear algebraic mathematical models for drone flight controls and the collective behaviors of flocks will increase the efficiency of drone maneuvers, allowing them to reorganize and fill gaps when one is removed. A MATLAB-based simulation was developed to model the behaviors using research conducted on the symmetric and synchronized behaviors observed from flocks of birds and simplified swarm intelligence parameters. The results show that utilizing a “fill the gap” model decreases blind spots and increases overall camera coverage during search and rescue observations, which is crucial in identifying people after natural disasters or major structural damages to infrastructure that require the need for search and rescue efforts.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Included in
Artificial Intelligence and Robotics Commons, Multi-Vehicle Systems and Air Traffic Control Commons, Systems Engineering and Multidisciplinary Design Optimization Commons
Accelerating Search and Rescue Response: A Simulation Study on the Dynamic Efficiency of Flocking-Enabled Drone Swarms
This project explores how imitations observed in animal group behavior, specifically flocking in birds, can be applied to the functionality of autonomous drone systems to aid in search and rescue efforts. The goal is to demonstrate how incorporating code based on the Boids, Vicsck and predictive control linear algebraic mathematical models for drone flight controls and the collective behaviors of flocks will increase the efficiency of drone maneuvers, allowing them to reorganize and fill gaps when one is removed. A MATLAB-based simulation was developed to model the behaviors using research conducted on the symmetric and synchronized behaviors observed from flocks of birds and simplified swarm intelligence parameters. The results show that utilizing a “fill the gap” model decreases blind spots and increases overall camera coverage during search and rescue observations, which is crucial in identifying people after natural disasters or major structural damages to infrastructure that require the need for search and rescue efforts.