Guidance, navigation, and control for autonomous flights of UAVs in denied environments
Abstract
This proposal focuses on the guidance, navigation, and control for autonomous flights of UAVs in denied environments for reconnaissance missions. The complex missions require UAVs with high performance to navigate autonomously in adverse environmental conditions and unknown terrains in which high communication interference, loss of communication, and sensor failures are presented. This problem is addressed in this proposal, which considers a research and development framework including phases, such as a mathematical model, GNC algorithm design, path planning, and reconnaissance, which involve theoretical methodologies. The UAV mathematical model will be obtained considering the Newton-Euler formulation, considering the disturbances due to wind gusts. The design of GNC algorithms for UAVs will be based on a geometric approach, obtaining a robust algorithm in which a guidance frame is considered to perform autonomous navigation. In this sense, linear and nonlinear control will be proposed to guarantee robustness against disturbances, unmodeled dynamics, and uncertainties. Path planning will be proposed to achieve optimized paths in both static and dynamic environments for real-time tasks, and it will be designed using genetic algorithms that help avoid static and mobile obstacles during autonomous flights. In this phase, the cooperative flight for UAVs will be addressed by considering the consensus approach. For reconnaissance, adeep learning method will be used to identify patterns in images and recognize objects so that the UAVs can perform robust navigation. The proposed GNC algorithm will guarantee robustness against interference in communications.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 10, 2025
- Source ID
- N629092512014
Entities
People
- Octavio Garcia Salazar
Organizations
- Office of Naval Research
- United States Navy
- Universidad Autónoma Nuevo León