  Motivated by applications where privacy is important, we consider planning
problems for robots acting in the presence of an observer. We first formulate
and then solve planning problems subject to stipulations on the information
divulged during plan execution --- the appropriate solution concept being both
a plan and an information disclosure policy. We pose this class of problem
under a worst-case model within the framework of procrustean graphs,
formulating the disclosure policy as a particular type of map on edge labels.
We devise algorithms that, given a planning problem supplemented with an
information stipulation, can find a plan, associated disclosure policy, or both
if some exists. Both the plan and associated disclosure policy may depend
subtlety on additional information available to the observer, such as whether
the observer knows the robot's plan (e.g., leaked via a side-channel). Our
implementation finds a plan and a suitable disclosure policy, jointly, when any
such pair exists, albeit for small problem instances.
