College - Author 1

College of Engineering

Department - Author 1

Electrical Engineering Department

Degree Name - Author 1

BS in Electrical Engineering

College - Author 2

College of Engineering

Department - Author 2

Electrical Engineering Department

Degree - Author 2

BS in Electrical Engineering

College - Author 3

College of Engineering

Department - Author 3

Electrical Engineering Department

Degree - Author 3

BS in Electrical Engineering

College - Author 4

College of Engineering

Department - Author 4

Electrical Engineering Department

Degree - Author 4

BS in Electrical Engineering

Date

6-2024

Primary Advisor

Siavash Farzan, College of Engineering, Electrical Engineering Department

Abstract/Summary

Drone swarms offer the potential to drastically reduce search times and improve the effectiveness of search and rescue operations. This senior project explores the development of a drone swarm system for search and rescue missions, focusing on two key challenges: (1) precise localization of each drone within the swarm relative to one another and (2) accurate localization of a target beacon relative to the drones. The project utilizes Real Time Kinematic (RTK) processing to enhance the accuracy of drone localization, achieving centimeter-level precision. Target localization is achieved through a triangulation-based approach using Received Signal Strength Indication (RSSI) data from a radio transmitter beacon. A leader-follower algorithm is implemented for formation control, enabling coordinated movement of the swarm towards the detected target. The project successfully demonstrates the feasibility of the proposed approach through simulations and field tests, highlighting the potential of drone swarms in revolutionizing search and rescue operations. Future work will focus on refining the algorithms, optimizing communication protocols, and expanding the swarm's capabilities to handle more complex search scenarios and a larger number of agents.

Included in

Robotics Commons

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