The goal of this project is to develop a simulation framework to streamline the testing and validation of AI-controlled aerial vehicles. The Artificial Intelligence (AI) design and verification flow consists of the digital environment creation process, an open-source AI-controlled autopilot, access to multiple open-source simulators, symbolic test generation engine, example test scenarios, and native design-for-experiment layer for each of the major subsystem of an AI-controlled aerial vehicle.
Project Details
Findings: The proof-of-concept demonstrated the viability of the system, with the low-fidelity simulation successfully flagging key scenarios for further testing, and the high-fidelity simulation providing accurate and realistic results for the flagged scenarios. By streamlining the testing process and focusing computational resources where they are most needed, this framework offers a robust solution for improving UAV safety and reliability in increasingly complex operational environments.
Research Team
Principal Investigators
M. Ilhan Akbas
Associate Professor, Associate Chair and Program Coord.
- Electrical Engineering and Computer Science Dept
- Daytona Beach College of Engineering