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
7-2026
Primary Advisor
Dale Dolan, College of Engineering, Electrical Engineering Department
Abstract/Summary
This senior project presents the design and implementation of a leader-election system for a leader-follower unmanned ground vehicle (UGV) swarm using embedded control and wireless communication. The objective of the project is to improve the robustness and mission longevity of a multi-agent robotic system by allowing the swarm to dynamically select the most suitable leader during operation. Each UGV is equipped with an ESP32 microcontroller, DWM1000 Ultra-Wideband (UWB) ranging modules, an MPU-6050 inertial measurement unit (IMU), motor drivers, and supporting power electronics to enable communication, sensing, and autonomous control. A battery monitoring subsystem was developed using the ESP32's built-in Analog-to-Digital Converter (ADC). Since the UGV battery voltage exceeds the ADC input range, a voltage divider was implemented to safely scale the battery voltage before measurement. Software was developed to average ADC readings, convert the measured voltage into a normalized battery level, and provide a reusable battery monitoring function for integration into the overall control system. This battery information serves as one of the primary inputs for future leader-election decisions. The proposed system utilizes centralized formation control, where the elected leader coordinates the movement of follower UGVs while maintaining a linear formation. If the leader becomes unavailable, the leader-election algorithm is designed to select a replacement based on vehicle health metrics such as battery level, communication quality, and motion stability. For convenient testing of the UGV formation, this project has developed an ESP32 base station that will broadcast start and stop commands to three other ESP32s as well as monitor their telemetry status. This project also investigates using a trained Support Vector Machine (SVM) to improve leader election accuracy based on past leader election data. The modular hardware and software architecture provides a scalable foundation for future research in autonomous swarm robotics, distributed embedded systems, and cooperative multi-agent control.
URL: https://digitalcommons.calpoly.edu/eesp/741