UAV-Based Search and Rescue in Avalanches using ARVA: An Extremum Seeking Approach

Abstract

This work deals with the problem of localizing a victim buried by an avalanche by means of a drone equipped with an ARVA (Appareil de Recherche de Victimes d'Avalanche) sensor. The proposed control solution is based on a "modelfree" extremum seeking strategy which is shown to succeed in steering the drone in a neighborhood of the victim position. The effectiveness and robustness of the proposed algorithm is tested in Gazebo simulation environment, where a new flight mode and a new controller module have been implemented as an extension of the well-known PX4 open source flight stack. Finally, to test usability, we present hardware-in-the-loop simulations on a Pixhawk 2 Cube board.

Multi-step dual control for exploration and exploitation in autonomous search with convergence guarantee

“…Inspired by biology, chemotaxis (Baker, Wolanin, & Stock, 2006) and anemotaxis (Chen, & Huang, 2020) search sources using chemical gradients and others as cue. By exploiting the fact that the maximum chemical concentration is located in the source location, extremum seeking has been adopted and developed into autonomous search where perturbation signal is added into the search action (Azzollini, Mimmo, Gentilini, & Marconi, 2021;Liu, & Krstic, 2010). A promising feature of the control driven search is that certain theoretic properties such as stability and convergence can be established under certain condition.…”