  We propose a new algorithm to simplify the controller development for
distributed robotic systems subject to external observations, disturbances, and
communication delays. Unlike prior approaches that propose specialized
solutions to handling communication latency for specific robotic applications,
our algorithm uses an arbitrary centralized controller as the specification and
automatically generates distributed controllers with communication management
and delay compensation. We formulate our goal as nonlinear optimal control --
using a regret minimizing objective that measures how much the distributed
agents behave differently from the delay-free centralized response -- and solve
for optimal actions w.r.t. local estimations of this objective using
gradient-based optimization. We analyze our proposed algorithm's behavior under
a linear time-invariant special case and prove that the closed-loop dynamics
satisfy a form of input-to-state stability w.r.t. unexpected disturbances and
observations. Our experimental results on both simulated and real-world robotic
tasks demonstrate the practical usefulness of our approach and show significant
improvement over several baseline approaches.
