Spanning-Tree Based Coverage for a Tethered Robot

Abstract

Tethered robots find widespread application in underwater and disaster recovery missions. This study focuses on the coverage path planning (CPP) problem for a tethered robot, considering cable constraints and the presence of forbidden areas in the environment. We propose adapting the spanning tree- based coverage algorithm to address CPP. Theoretical complexity analysis reveals NP-completeness in cases involving forbidden areas. We show how to solve CPP by searching for a tree in a configuration graph, and how to reduce the size of this graph to compute approximate solutions faster. We introduce Integer Linear Programming (ILP) models corresponding to these approximations and experimentally compare them on various instances.