  Suppose an agent asserts that it will move through an environment in some
way. When the agent executes its motion, how does one verify the claim? The
problem arises in a range of contexts including in validating safety claims
about robot behavior, applications in security and surveillance, and for both
the conception and the (physical) design and logistics of scientific
experiments. Given a set of feasible sensors to select from, we ask how to
choose sensors optimally in order to ensure that the agent's execution does
indeed fit its pre-disclosed itinerary. Our treatment is distinguished from
prior work in sensor selection by two aspects: the form the itinerary takes (a
regular language of transitions) and that families of sensor choices can be
grouped as a single choice. Both are intimately tied together, permitting
construction of a product automaton because the same physical sensors (i.e.,
the same choice) can appear multiple times. This paper establishes the hardness
of sensor selection for itinerary validation within this treatment, and
proposes an exact algorithm based on an ILP formulation that is capable of
solving problem instances of moderate size. We demonstrate its efficacy on
small-scale case studies, including one motivated by wildlife tracking.
