Planning for Autonomous Planetary Vehicles

Autonomous vehicles are often complex systems that work in a partially unknown environment, with narrow energy/time/movement constraints. 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 a model checking based tool, namely UPMurphi, can be used to generate optimal plans to control the engine of an autonomous planetary vehicle, working directly on its hybrid model, and thus achieving very accurate results.