  This paper proposes an algorithmic method to heuristically solve the famous
Travelling Salesman Problem (TSP) when the salesman's path evolves in
continuous state space and discrete time but with otherwise arbitrary
(nonlinear) dynamics. The presented method is based on the framework of
Symbolic Control. In this way, our method returns a provably correct
state-feedback controller for the underlying coverage specification, which is
the TSP leaving out the requirement for optimality on the route. In addition,
we utilize the Lin-Kernighan-Helsgaun TSP solver to heuristically optimize the
cost for the overall taken route. Two examples, an urban parcel delivery task
and a UAV reconnaissance mission, greatly illustrate the powerfulness of the
proposed heuristic.
