RESOURCE-OPTIMAL PLANNING FOR AN AUTONOMOUS PLANETARY VEHICLE

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