TY - JOUR A1 - Neumann, Patrick P. A1 - Bennetts, V.H. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias A1 - Schiller, J.H. T1 - Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms N2 - 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. KW - Autonomous micro UAV KW - Chemical and wind sensing KW - Gas source localization KW - Particle filter PY - 2013 U6 - https://doi.org/10.1080/01691864.2013.779052 SN - 0169-1864 SP - 725 EP - 738 PB - VNU Sciences Pr. CY - Utrecht AN - OPUS4-28010 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Schnürmacher, M. A1 - Bennetts, V.H. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias A1 - Schiller, J.H. T1 - A probabilistic gas patch path prediction approach for airborne gas ource localization in non-uniform wind fields N2 - 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 for GSL that is based on a particle filter (PF). Simulation and real-world experiments demonstrate the suitability of this algorithm for micro UAV platforms. T2 - ISOEN 2013 - 15th International symposium on olfaction and electronic nose CY - Deagu, South Korea DA - 02.07.2013 KW - Autonomous micro UAV KW - Chemical and wind sensing KW - Gas source localization KW - Particle filter PY - 2013 IS - Symposia / Applications of remote and local gas sensing ... SP - 15 EP - 16 AN - OPUS4-28878 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Neumann, Patrick P. A1 - Schnürmacher, M. A1 - Bennetts, V.H. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias A1 - Schiller, J.H. T1 - A probabilistic gas patch path prediction approach for airborne gas source localization in non-uniform wind fields N2 - 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. KW - Autonomous micro UAV KW - Chemical and wind sensing KW - Gas source localization KW - Particle filter PY - 2014 U6 - https://doi.org/10.1166/sl.2014.3168 SN - 1546-198X SN - 1546-1971 VL - 12 IS - 6/7 SP - 1113 EP - 1118 PB - American Scientific Publishers (ASP) CY - Stevenson Ranch, CA, USA AN - OPUS4-31525 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -