  Temporal logic can be used to formally specify autonomous agent goals, but
synthesizing planners that guarantee goal satisfaction can be computationally
prohibitive. This paper shows how to turn goals specified using a subset of
finite trace Linear Temporal Logic (LTL) into a behavior tree (BT) that
guarantees that successful traces satisfy the LTL goal. Useful LTL formulas for
achievement goals can be derived using achievement-oriented task mission
grammars, leading to missions made up of tasks combined using LTL operators.
Constructing BTs from LTL formulas leads to a relaxed behavior synthesis
problem in which a wide range of planners can implement the action nodes in the
BT. Importantly, any successful trace induced by the planners satisfies the
corresponding LTL formula. The usefulness of the approach is demonstrated in
two ways: a) exploring the alignment between two planners and LTL goals, and b)
solving a sequential key-door problem for a Fetch robot.
