College - Author 1

College of Engineering

Department - Author 1

Mechanical Engineering Department

Degree Name - Author 1

BS in Mechanical Engineering

College - Author 2

College of Engineering

Department - Author 2

Mechanical Engineering Department

Degree - Author 2

BS in Mechanical Engineering

College - Author 3

College of Engineering

Department - Author 3

Mechanical Engineering Department

Degree - Author 3

BS in Mechanical Engineering

College - Author 4

College of Engineering

Department - Author 4

Mechanical Engineering Department

Degree - Author 4

BS in Mechanical Engineering

Date

6-2025

Primary Advisor

Rick Lasko, College of Engineering, Mechanical Engineering Department

Abstract/Summary

Autonomous vehicles have been starting to address real-world issues through innovative technology. RTX (Raytheon) needs a way to have two autonomous vehicles, an unmanned air vehicle (UAV), and unmanned ground vehicle (UGV) reliably communicate with each other with the goal of landing and delivering a payload to designated delivery zones. This will foster creativity, innovation, and team-solving skills. Additionally, it will also promote & strengthen university relationships, evaluate top graduates, and promote corporate branding.

This report details the design process of a UAV-UGV delivery system developed for the RTX Autonomous Vehicle Competition (AVC). The system features a custom-built hexacopter UAV and a modified Overlander-4 UGV, both engineered for autonomous payload transport within a 90 ft × 90 ft arena. Final design decisions were driven by performance modeling, weight constraints, and mission requirements. The UAV employs T-Motor MN501-S 360 KV motors with 16×5.5” APC propellers, optimized for a 25 lb takeoff weight and over 20 minutes of flight time. The UGV uses an inclined ramp with closed-loop servo control for reliable, low-power payload deployment. Key priorities included FAA compliance, efficient power usage, and robust system integration. The result is a cost-effective, modular platform showcasing reliable autonomy and interdisciplinary engineering design.

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