Honors Theses
Advisor
Nicholas M. Stiffler, Ph.D.
Department
Computer Science
Publication Date
4-22-2026
Document Type
Honors Thesis
Abstract
Advanced UAV missions, such as infrastructure inspection and disaster-zone sensing, are fundamentally constrained by limited onboard battery capacity. Conventional flight planners typically optimize for shortest distance, despite the fact that maneuver-dependent energy costs vary substantially and make distance a poor proxy for power consumption. This thesis develops an energy-centric routing framework that applies an action-weighted energy heuristic to formulate and solve an Energy-Minimized Vehicle Routing Problem (EM-VRP). In addition, it examines the joint optimization of vehicle energy expenditure and data freshness to ensure timely revisitation of spatial nodes. The framework is implemented through custom mission-planning software and validated on physical hardware using real-time energy monitoring. Results show that, relative to traditional distance-based planning, the proposed method reduces overall power usage and enables longer, more comprehensive autonomous scans in complex 3D environments.
Permission Statement
This item is protected by copyright law (Title 17, U.S. Code) and may only be used for noncommercial, educational, and scholarly purposes.
Keywords
Undergraduate research
eCommons Citation
Kuederle, Ryan, "EM-VRP: Energy-Minimizing Vehicle Routing Planning for Maneuver-Aware UAV Routing" (2026). Honors Theses. 511.
https://ecommons.udayton.edu/uhp_theses/511
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