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
Date
6-2026
Primary Advisor
Siavash Farzan, College of Engineering, Electrical Engineering Department
Abstract/Summary
Micro-UAVs have seen growing use in applications such as search and rescue, agriculture monitoring, and military reconnaissance, especially when utilized in swarms. To maintain control and proper formation within a swarm, micro-UAVs typically rely on positioning systems, such as GPS, to determine their locations relative to one another. However, these positioning systems are not always available, such as in indoor environments or situations involving GPS jamming. Additionally, GPS lacks the precision to discern the exact position of micro-UAVs flying closely together. This project aims to address these issues by using cooperative localization as a replacement for GPS and other positioning systems. Simply put, cooperative localization is a method in which robotic agents in a network share sensor data and relative measurements to come to a consensus on a singular global frame, enabling them to know the exact position of all agents relative to that frame. This technique can be applied to any robotic network involving multiple moving agents, not just micro-UAVs. This project, however, focuses on micro-UAVs, using the Crazyflie drone platform to conduct experiments and validate results on real hardware. To streamline testing and improve safety, a Python-based simulation framework is used to model drone behavior before performing real-world experiments. This project uses three Crazyflie drones to demonstrate coordinated formation control and movement while collecting real-flight telemetry for cooperative-localization evaluation. Quantitative evaluation is performed using Lighthouse-based ground-truth trajectories, from which inter-agent measurements are synthesized and processed by the proposed estimator. This implementation provides a practical platform for studying GPS-independent swarm localization and establishes a foundation for future closed-loop cooperative-localization control.
URL: https://digitalcommons.calpoly.edu/eesp/731