Designing robust quadcopter software based on a real-time partitioned operating system and formal verification techniques

The creation of reliable unmanned aerial vehicles (drones) now is an important task in the science and technology, because such devices can have a lot of use-cases in the digital economy and modern life, so we need to ensure the reliability here. In this article, it is proposed to assemble a quadcopter from low-cost components in order to obtain a hardware prototype and to develop a software solution for the flight controller with high-reliability requirements, which will meet avionics software standards using existing open-source software solutions, and also apply the results as a model for teaching courses “Components of operating systems” and “Software verification”. In the study, we proceed to analyse the structure of quadcopters and flight controllers for them, represent a self-assembly solution. We describe Ardupilot as open-source software for unmanned aerial vehicles, the appropriate APM controller and methods of PID control. Today's avionics standard of reliable software for flight controllers is a real-time partitioning operating system that is capable of responding to events from devices with an expected speed, as well as sharing processor time and memory between isolated partitions. A good example of such OS is the open-source POK (Partitioned Operating Kernel). In the repository, it contains an example design of a system for the quadcopters using AADL language for modeling its hardware and software. We apply such a technique with Model-driven engineering to a demo system that runs on real hardware and contains a flight management process with PID control as a partitioned process. Using a partitioned OS brings the reliability of flight system software to the next level. And to increase the level of control logic correctness we propose to use formal verification methods and provide examples of verifiable properties at the level of code using the deductive approach as well as at the level of the cyber-physical system using Differential dynamic logic to prove the stability.