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While AI techniques have found many successful applications in autonomoussystems, many of them permit behaviours that are difficult to interpret and maylead to uncertain results. We follow the "verification as planning" paradigmand propose to use model checking techniques to solve planning and goalreasoning problems for autonomous systems. We give a new formulation of GoalTask Network (GTN) that is tailored for our model checking based framework. Wethen provide a systematic method that models GTNs in the model checker ProcessAnalysis Toolkit (PAT). We present our planning and goal reasoning system as aframework called Goal Reasoning And Verification for Independent TrustedAutonomous Systems (GRAVITAS) and discuss how it helps provide trustworthyplans in an uncertain environment. Finally, we demonstrate the proposed ideasin an experiment that simulates a survey mission performed by the REMUS-100autonomous underwater vehicle.

GRAVITAS: A Model Checking Based Planning and Goal Reasoning Framework for Autonomous Systems