  Autonomous planetary vehicles, also known as rovers, are small autonomous
vehicles equipped with a variety of sensors used to perform exploration and
experiments on a planet's surface. Rovers work in a partially unknown
environment, with narrow energy/time/movement constraints and, typically, small
computational resources that limit the complexity of on-line planning and
scheduling, thus they represent a great challenge in the field of autonomous
vehicles. Indeed, formal models for such vehicles usually involve hybrid
systems with nonlinear dynamics, which are difficult to handle by most of the
current planning algorithms and tools. Therefore, when offline planning of the
vehicle activities is required, for example for rovers that operate without a
continuous Earth supervision, such planning is often performed on simplified
models that are not completely realistic. In this paper we show how the
UPMurphi model checking based planning tool can be used to generate
resource-optimal plans to control the engine of an autonomous planetary
vehicle, working directly on its hybrid model and taking into account several
safety constraints, thus achieving very accurate results.
