학술논문

Formal Verification for Safe AI-based Flight Planning for UAVs*
Document Type
Conference
Source
2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W) DSN-W Dependable Systems and Networks Workshops (DSN-W), 2023 53rd Annual IEEE/IFIP International Conference on. :275-282 Jun, 2023
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Robotics and Control Systems
Transportation
Measurement
Autonomous aerial vehicles
Sensor systems
Robustness
Planning
Safety
Sensors
Formal verification
theorem proving
SMT-based verification
Temporal plan network
Remotely Piloted Aircraft (RPA)
Flight planning component
Language
ISSN
2325-6664
Abstract
Planning and decision-making, especially the planning of collision-free paths, are an integral part of the operation of Unmanned Aerial Vehicles (UAVs). Formalisms like Temporal Plan Networks (TPN) can be used to provide optimal flight plans for UAVs. However, ensuring that the generated flight plans are safe can be a complex task, depending on the method used to generate the plans. Safe in this context means that the next planned action for the UAV does not violate safety constraints, for example, no-fly zones (NFZ). In this paper, we investigate the application of formal methods to generate metrics that could be used as assurance evidence in the argumentation of the safety of the planning component. In particular, we make use of Satisfiability Modulo Theories (SMT)-based verification to verify low-level requirements, together with Program Verification System (PVS) to check the design requirements of the AI-based planning component.