  Desensitization addresses safe optimal planning under parametric
uncertainties by providing sensitivity function-based risk estimates. This
paper expands upon the existing work on desensitization in optimal control to
address safe planning for a class of two-player differential games. In the
proposed game, parametric uncertainties correspond to variations of the model
parameters for each player about their nominal values. The two players in the
proposed formulation are assumed to have perfect information about these
nominal parameter values. However, it is assumed that only one of the players
has complete knowledge of the actual parameter value, resulting in information
asymmetry in the proposed game. This lack of knowledge regarding the parameter
variations is expected to result in state constraint violations for the player
with an information disadvantage. In this regard, a desensitized feedback
strategy that provides safe trajectories is proposed for the player with
incomplete information. The proposed feedback strategy is evaluated for
instances involving a single pursuer and a single evader with an uncertain
moving obstacle, where the pursuer is assumed to only know the nominal value of
the obstacle's speed. At the same time, the evader knows the obstacle's true
speed, and also the fact that the pursuer knows only the nominal value of the
obstacle's speed. Subsequently, deceptive strategies are proposed for the
evader, who has an information advantage, and these strategies are assessed
against the pursuer's desensitized strategy.
