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

On the Solution of the Travelling Salesman Problem for Nonlinear Salesman Dynamics using Symbolic Optimal Control