  We present a hybrid control framework for solving a motion planning problem
among a collection of heterogenous agents. The proposed approach utilizes a
finite set of low-level motion primitives, each based on a piecewise affine
feedback control, to generate complex motions in a gridded workspace. The
constraints on allowable sequences of successive motion primitives are
formalized through a maneuver automaton. At the higher level, a control policy
generated by a shortest path non-deterministic algorithm determines which
motion primitive is executed in each box of the gridded workspace. The overall
framework yields a highly robust control design on both the low and high
levels. We experimentally demonstrate the efficacy and robustness of this
framework for multiple quadrocopters maneuvering in a 2D or 3D workspace.
