Formal Verification of Probabilistic Multi-Agent Systems for Ballistic Rocket Flight Using Probabilistic Alternating-Time Temporal Logic

2025-11-27

AI Summary

To address trajectory deviation and unauthorized landing risks in ballistic rocket microgravity experiments, this paper proposes a formal verification method for probabilistic multi-agent systems. We construct a probabilistic state-transition model incorporating meteorological uncertainties, calibrated against real telemetry data. For the first time, Probabilistic Alternating-time Temporal Logic (PATL) is employed to formally specify and verify critical safety properties—including trajectory constraints, no-fly zone avoidance, and emergency engine shutdown triggering—under multi-agent coordination. We design an automated PATL verification framework capable of detecting deviations and landing risks in real time, with integrated monitoring and engine shutdown actuation. Experimental evaluation demonstrates that the method ensures mission safety and scientific objective fulfillment under complex environmental disturbances, achieving significant improvements in verification accuracy and response latency.

Technology Category

• Multiagent Systems: Multiagent Systems under Uncertainty
• Reasoning under Uncertainty: Uncertainty Representations
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

This technical report presents a comprehensive formal verification approach for probabilistic agent systems modeling ballistic rocket flight trajectories using Probabilistic Alternating-Time Temporal Logic (PATL). We describe an innovative verification framework specifically designed for analyzing critical safety properties of ballistic rockets engineered to achieve microgravity conditions for scientific experimentation. Our model integrates authentic flight telemetry data encompassing velocity vectors, pitch angles, attitude parameters, and GPS coordinates to construct probabilistic state transition systems that rigorously account for environmental stochasticity, particularly meteorological variability. We formalize mission-critical safety properties through PATL specifications to systematically identify trajectory deviation states where the rocket risks landing in prohibited or hazardous zones. The verification framework facilitates real-time safety monitoring and enables automated intervention mechanisms, including emergency engine disengagement protocols, when predefined safety thresholds are exceeded. Experimental validation demonstrates the practical effectiveness and reliability of our approach in ensuring mission safety while maintaining scientific mission objectives.

Problem

• Verifies safety of probabilistic multi-agent rocket systems
• Models flight trajectories using real telemetry and environmental data
• Identifies hazardous deviations to enable real-time interventions

Innovation

• PATL formal verification for rocket safety properties
• Integration of flight telemetry into probabilistic transition systems
• Real-time monitoring with automated emergency intervention mechanisms