This paper addresses the problem to simulate ARVA sensors using ROS and Gazebo. ARVA is a French acronym which stands for Appareil de Recherche de Victims en Avalanche and represents the forefront technology adopted in Search & Rescue operations to localize victims of avalanches buried under the snow. The aim of this paper is to describe the mathematical and theoretical background of the transceiver, discussing its implementation and integration with ROS allowing researchers to develop faster and smarter Search &Rescue strategies based on ARVA receiver data. To assess the effectiveness of the proposed sensor model, We present a simulation scenario in which an Unmanned Aerial Vehicle equipped with the transceiver sensor performs a basic S&R pattern using the output of ARVA system.

This paper introduces a new approach for victim localization in avalanches that will be exploited by UAVs using the ARVA sensor. We show that the nominal ARVA measurement can be linearly related to a quantity that is sufficient to reconstruct the victim position. We explicitly deal with a robust scenario in which the measurement is actually perturbed by a noise that grows with the distance to the victim and we propose an adaptive control scheme made of a least-square identifier and a trajectory generator whose role is both to guarantee the persistence of excitation for the identifier and to steer the ARVA receiver towards the victim. We show that the system succeeds in localizing the victim in a domain where the ARVA output is sufficiently informative and illustrate its performance in simulation. This new approach could significantly reduce the searching time by providing an exploitable estimate before having reached the victim. The work is framed within the EU project AirBorne whose goals is to develop at TRL8 a drone for quick localization of victims in avalanche scenarios.

This paper presents the autonomous battery exchange operation for small scale UAVs, using a mobile ground base that carries a robotic arm and a service station containing the battery exchange mechanism. The goal of this work is to demonstrate the means to increase the autonomy and persistence of robotic systems without requiring human intervention. The design and control of the system and its components are presented in detail, as well as the collaborative software framework used to plan and execute complex missions. Finally, the results of autonomous outdoor experiments are presented, in which the ground rover successfully localizes, retrieves, services, and deploys the landed UAV, proving its capacity to extend and enhance autonomous operations.