  This paper presents an algorithmic framework for control synthesis of
continuous dynamical systems subject to signal temporal logic (STL)
specifications. We propose a novel algorithm to obtain a time-partitioned
finite automaton from an STL specification, and introduce a multi-layered
framework that utilizes this automaton to guide a sampling-based search tree
both spatially and temporally. Our approach is able to synthesize a controller
for nonlinear dynamics and polynomial predicate functions. We prove the
correctness and probabilistic completeness of our algorithm, and illustrate the
efficiency and efficacy of our framework on several case studies. Our results
show an order of magnitude speedup over the state of the art.
