Executive Summary
This thesis presents an optimal trajectory generation algorithm for real-time coordination and control of multiple quadrotor UAVs. Designed for indoor intelligence, surveillance, and reconnaissance (ISR) missions where GPS is unreliable, the algorithm enables autonomous operation with minimal user input. It integrates trajectory planning, following, and multi-vehicle coordination, validated through experimental data.
Why It Matters
This document is crucial for defense analysts as it details advanced control algorithms for multi-quadrotor UAVs, directly impacting future military ISR capabilities and autonomous swarm operations in GPS-denied environments.
Key Takeaways
- The thesis develops an optimal trajectory generation algorithm for real-time control of multiple quadrotor UAVs.
- The system is designed for autonomous ISR missions in indoor or GPS-denied environments, requiring minimal user input.
- It integrates trajectory planning, following, and multi-vehicle coordination, validated through experimental data.
- The research leverages existing trajectory following controllers while focusing on generation and coordination.
- The approach allows for fully autonomous systems with user input only at mission initiation.
Strategic Relevance
The development of autonomous multi-quadrotor UAV systems for ISR in GPS-denied environments significantly enhances military operational capabilities. This technology can provide critical intelligence in complex urban or indoor settings, reducing human risk and increasing efficiency for reconnaissance and surveillance tasks.