
## Resource-Optimal P**Lanning For An** Autonomous Planetary V**Ehicle**

Giuseppe Della Penna1, Benedetto Intrigila2 **, Daniele Magazzeni**3 and Fabio Mercorio1 1**Department of Computer Science, University of L'Aquila, L'Aquila - Italy** 
giuseppe.dellapenna@univaq.it, fabio.mercorio@univaq.it 2**Department of Mathematics, University of Rome "Tor Vergata", Rome - Italy** 
intrigil@mat.uniroma2.it 3**Department of Science, University of Chieti, Chieti - Italy** 
magazzeni@sci.unich.it 

## A**Bstract**

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. 

## K**Eywords**

AI Planning, Autonomous Vehicles, Model Checking 

## 1. I**Ntroduction**

Autonomous planetary vehicles, or rovers, are a great challenge in the field of autonomous vehicles, since they have often to take actions on a hazardous ground with narrow time and energy consumption constraints. Rovers operating on distant planets may receive commands from Earth operators only once per day, and during the remaining time they have to perform a specific mission, which may include moving to a specific place, position some instruments, take measures, etc [1], [2]. 

Usually, rover activities are organised on the ground into a detailed plan that, once generated and uploaded to the vehicle, drives it for the rest of the mission. Typically, in this situation, if the rover encounters an unexpected (i.e., not contained in the mission plan) situation, it stops and waits for further Earth instructions, possibly wasting a lot of time. Therefore, planning for this kind of autonomous vehicles should be very precise and take into consideration many factors [3]. 

As noted, many rover activities begin with a movement that places it in a specified location. 

Thus, independently from the nature of the rover's mission, reaching the activity location is the first goal to achieve, and it must satisfy two main constraints: energy and time consumption. Indeed, at the end of the journey, rover batteries must still contain enough charge to perform the 