No abstract

In order to rigorously analyze mission plans, they have to be translated into a tractable formalism. This paper proposes to use the description logic Attributive Language with Complements and concrete Domains ALC(D) as the input formalism for a mission plan based on behavior trees. The interface is described using the safety circuit of an exemplary unmanned aerial vehicle. The system is executed using a three-degree-of-freedom simulation model. Results indicate that the system can be used as a first step towards verification of mission plans with formal methods. In a more efficient variant, the behavior tree mission plan executes sufficiently fast to be deployed in actual flight computers.

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The paper introduces a continuous-time architecture and a Modelica library for mission planning based on behavior trees. It allows to study the long-time behavior of complex aircraft models in interaction with reactive mission plans by means of efficient simulations. The developed Modelica library is used in a mission example for a solar high-altitude aircraft and the advantages of the behavior tree formulation in both simulation speed and modularity are discussed. The architecture will further be used to deploy automatically coded mission plans to actual flight computers using the functional mockup interface.

The behavior tree formalism as introduced recently to the application of mission management of unmanned aerial vehicles does provide for internal memory of mission plans. This is an important drawback for even simple plans such as waypoint sequences, because the information about visited waypoints must be stored outside of the plan execution engine. In this paper, two approaches are presented in order to provide tasks with states inside behavior trees: The first allows to embed regular state machines in a specialized behavior tree task. The second provides new memory and reset tasks in order to store information directly in the tree. Both approaches are shown to solve the waypoint following plan and promise to be applicable to a much broader range of mission management problems.