  In large scale coverage operations, such as marine exploration or aerial
monitoring, single robot approaches are not ideal, as they may take too long to
cover a large area. In such scenarios, multi-robot approaches are preferable.
Furthermore, several real world vehicles are non-holonomic, but can be modeled
using Dubins vehicle kinematics. This paper focuses on environmental monitoring
of aquatic environments using Autonomous Surface Vehicles (ASVs). In
particular, we propose a novel approach for solving the problem of complete
coverage of a known environment by a multi-robot team consisting of Dubins
vehicles. It is worth noting that both multi-robot coverage and Dubins vehicle
coverage are NP-complete problems. As such, we present two heuristics methods
based on a variant of the traveling salesman problem -- k-TSP -- formulation
and clustering algorithms that efficiently solve the problem. The proposed
methods are tested both in simulations to assess their scalability and with a
team of ASVs operating on a lake to ensure their applicability in real world.
