Dokument-ID Dokumenttyp Autoren/innen Persönliche Herausgeber/innen Haupttitel Abstract Auflage Verlagsort Verlag Herausgeber (Institution) Erscheinungsjahr Titel des übergeordneten Werkes Jahrgang/Band ISBN Veranstaltung Veranstaltungsort Beginndatum der Veranstaltung Enddatum der Veranstaltung Ausgabe/Heft Erste Seite Letzte Seite URN DOI Lizenz Datum der Freischaltung OPUS4-28010 Zeitschriftenartikel Neumann, Patrick P.; Bennetts, V.H.; Lilienthal, A.J.; Bartholmai, Matthias; Schiller, J.H. Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms Gas source localization (GSL) with mobile robots is a challenging task due to the unpredictable nature of gas dispersion, the limitations of the currents sensing technologies, and the mobility constraints of ground-based robots. This work proposes an integral solution for the GSL task, including source declaration. We present a novel pseudo-gradient-based plume tracking algorithm and a particle filter-based source declaration approach, and apply it on a gas-sensitive micro-drone. We compare the performance of the proposed system in simulations and real-world experiments against two commonly used tracking algorithms adapted for aerial exploration missions. Utrecht VNU Sciences Pr. 2013 Advanced robotics 725 738 10.1080/01691864.2013.779052 2016-02-20 OPUS4-25773 Zeitschriftenartikel Neumann, Patrick P.; Asadi, S.; Lilienthal, A.J.; Bartholmai, Matthias; Schiller, J.H. Autonomous gas-sensitive microdrone - wind vector estimation and gas distribution mapping This article presents the development and validation of an autonomous, gas sensitive microdrone that is capable of estimating the wind vector in real time using only the onboard control unit of the microdrone and performing gas distribution mapping (DM). Two different sampling approaches are suggested to address this problem. On the one hand, a predefined trajectory is used to explore the target area with the microdrone in a real-world gas DM experiment. As an alternative sampling approach, we introduce an adaptive strategy that suggests next sampling points based on an artificial potential field (APF). Initial results in real-world experiments demonstrate the capability of the proposed adaptive sampling strategy for gas DM and its use for gas source localization. New York, NY, USA IEEE 2012 IEEE Robotics and automation magazine 19 1 50 61 10.1109/MRA.2012.2184671 2016-02-19 OPUS4-31525 Zeitschriftenartikel Neumann, Patrick P.; Schnürmacher, M.; Bennetts, V.H.; Lilienthal, A.J.; Bartholmai, Matthias; Schiller, J.H. A probabilistic gas patch path prediction approach for airborne gas source localization in non-uniform wind fields In this paper, we show that a micro unmanned aerial vehicle (UAV) equipped with commercially available gas sensors can address environmental monitoring and gas source localization (GSL) tasks. To account for the challenges of gas sensing under real-world conditions, we present a probabilistic approach to GSL that is based on a particle filter (PF). Simulation and real-world experiments demonstrate the suitability of this algorithm for micro UAV platforms. Stevenson Ranch, CA, USA American Scientific Publishers (ASP) 2014 Sensor letters 12 6/7 1113 1118 10.1166/sl.2014.3168 2016-02-20