TY - CONF A1 - Neumann, Patrick P. A1 - Bennetts, V.H. A1 - Bartholmai, Matthias T1 - Adaptive gas source localization strategies and gas distribution mapping using a gas-sensitive micro-drone N2 - In this paper we exemplify how to address environmental monitoring tasks with a gas-sensitive micro-drone and present two different approaches to locate gas emission sources. First, we sent the micro-drone in real-world experiments along predefined sweeping trajectories to model the gas distribution. The identification of the gas source location is made afterwards based on the created model. Second, we adapted two bio-inspired plume tracking algorithms that have been implemented so far on ground-based mobile robots. We developed a third bio-inspired algorithm, which is called “pseudo gradient-based algorithm”, and compared its perfomance in real-world experiments with the other two algorithms. Keywords: Anemotaxis, chemotaxis, micro UAV, bio-inspired, chemical sensing, gas distribution modeling, gas source localization, gas sensors, mobile sensing system, odor localization, olfaction, plume tracking, quadrocopter. T2 - 16. GMA/ITG-Fachtagung 'Sensoren und Messsysteme' CY - Nürnberg, Germany DA - 22.05.2012 KW - Anemotaxis KW - Chemotaxis KW - Micro UAV KW - Bio-inspired KW - Chemical sensing KW - Gas distribution modeling KW - Gas source localization KW - Gas sensors KW - Mobile sensing system KW - Odor localization KW - Olfaction KW - Plume tracking KW - Quadrocopter PY - 2012 SN - 978-3-9813484-0-8 DO - https://doi.org/10.5162/sensoren2012/P5.4 SP - 800 EP - 809 CY - Wunstorf AN - OPUS4-26004 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Neumann, Patrick P. A1 - Asadi, S. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias A1 - Schiller, J.H. T1 - Autonomous gas-sensitive microdrone - wind vector estimation and gas distribution mapping N2 - 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. KW - Anemometric sensor KW - Autonomous micro UAV KW - Chemical sensing KW - Gas distribution modelling KW - Gas source localization KW - Gas sensors KW - Mobile sensing system KW - Quadrocopter KW - Sensor planning KW - Artificial potential field PY - 2012 DO - https://doi.org/10.1109/MRA.2012.2184671 SN - 1070-9932 VL - 19 IS - 1 SP - 50 EP - 61 PB - IEEE CY - New York, NY, USA AN - OPUS4-25773 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -