Real-Time Guaranteed Monitoring for a Drone Using Interval Analysis and Signal Temporal Logic

This paper presents a guaranteed model-based approach for monitoring drone trajectory, providing real-time guarantees with a simplified dynamic model. ROS components are introduced for real-time implementation, enabling monitoring and adjustments in both simulations and actual systems. We extend the application of set-based simulation by formalizing timing conditions with Signal Temporal Logic (STL) and incorporating Boolean interval arithmetic to handle undetermined behaviors. The method compares model-based fault prediction using a stochastic approach with a set-based method, which manages bounded uncertainties and offers guarantees. Experimental validation, including comparisons against Monte Carlo methods, demonstrates the approach ability to ensure safety in worst-case scenarios while remaining suitable for real-time processing.