TY - CONF A1 - Neumann, Patrick P. A1 - Bennetts, V. H. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias T1 - From Insects to Micro Air Vehicles - A Comparison of Reactive Plume Tracking Strategies N2 - Insect behavior is a common source of inspiration for roboticists and computer scientists when designing gas-sensitive mobile robots. More specifically, tracking airborne odor plumes and localization of distant gas sources are abilities that suit practical applications such as leak localization and emission monitoring. Gas sensing with mobile robots has been mostly addressed with ground-based platforms and under simplified conditions and thus, there exist a significant gap between the outstanding insect abilities and state of the art robotics systems. As a step towards practical applications, we evaluated the performance of three biologically inspired plume tracking algorithms. The evaluation is carried out not only with computer simulations, but also with real-world experiments in which, a quadrocopter-based micro Unmanned Aerial Vehicle autonomously follows a methane trail towards the emitting source. Compared to ground robots, micro UAVs bring several advantages such as their superior steering capabilities and fewer mobility restrictions in complex terrains. The experimental evaluation shows that, under certain environmental conditions, insect like behavior in gas-sensitive UAVs is feasible in real world environments. T2 - 13th International Conference on Intelligent Autonomous Systems (IAS) CY - Padova, Italy DA - 15.07.2014 KW - Autonomous micro UAV KW - Mobile robot olfaction KW - Gas source localization KW - Reactive plume tracking KW - Biologically inspired robots PY - 2014 SP - 1 EP - 12 AN - OPUS4-43920 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 DO - 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 - TY - CONF A1 - Neumann, Patrick P. A1 - Bennetts, V.H. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias T1 - From insects to micro air vehicles - a comparison of reactive plume tracking strategies N2 - Insect behavior is a common source of inspiration for roboticists and computer scientists when designing gas-sensitive mobile robots. More specifically, tracking airborne odor plumes, and localization of distant gas sources are abilities that suit practical applications such as leak localization and emission monitoring. Gas sensing with mobile robots has been mostly addressed with ground-based platforms and under simplified conditions and thus, there exist a significant gap between the outstanding insect abilities and state-of-the-art robotics systems. As a step toward practical applications, we evaluated the performance of three biologically inspired plume tracking algorithms. The evaluation is carried out not only with computer simulations, but also with real-world experiments in which, a quadrocopter-based micro Unmanned Aerial Vehicle autonomously follows a methane trail toward the emitting source. Compared to ground robots, micro UAVs bring several advantages such as their superior steering capabilities and fewer mobility restrictions in complex terrains. The experimental evaluation shows that, under certain environmental conditions, insect like behavior in gas-sensitive UAVs is feasible in real-world environments. T2 - IAS13 - 13th International conference on intelligent autonomous systems CY - Padova, Italy DA - 2014-07-15 KW - Autonomous micro UAV KW - Mobile robot olfaction KW - Gas source localization KW - Reactive plume tracking KW - Biologically inspired robots PY - 2016 SN - 978-3-319-08338-4; 978-3-319-08337-7 DO - https://doi.org/10.1007/978-3-319-08338-4_110 SN - 2194-5357 SP - 1533 EP - 1548 PB - Springer Verlag CY - Berlin, Germany AN - OPUS4-31526 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Asadi, S. A1 - Schiller, J.H. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias T1 - An artificial potential field based sampling strategy for a gas-sensitive micro-drone N2 - This paper presents a sampling strategy for mobile gas sensors. Sampling points are selected using a modified artificial potential field (APF) approach, which balances multiple criteria to direct sensor measurements towards locations of high mean concentration, high concentration variance and areas for which the uncertainty about the gas distribution model is still large. By selecting in each step the most often suggested close-by measurement location, the proposed approach introduces a locality constraint that allows planning suitable paths for mobile gas sensors. Initial results in simulation and in real-world experiments with a gas-sensitive micro-drone demonstrate the suitability of the proposed sampling strategy for gas distribution mapping and its use for gas source localization. T2 - IEEE/RSJ International conference on intelligent robots and systems (IROS '11) / Workshop on robotics for environmental monitoring (WREM2011) CY - San Francisco, CA, USA DA - 25.09.2011 KW - Autonomous 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 - 2011 SP - 34 EP - 38 AN - OPUS4-24537 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 - 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 DO - 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 - Winkler, Nicolas P. A1 - Nerger, Tino A1 - Lohrke, Heiko A1 - Bartholmai, Matthias T1 - Robotic Olfaction in Action: Field Applications and Results from Current Research N2 - In recent decades, robotics, particularly in environmental monitoring, has made significant advances. Robots of various forms and sizes have become essential tools for data collection in environmental research. Mobile Robot Olfaction (MRO) involves mobile robots equipped with gas sensors and requires the integration of multiple disciplines, including signal processing, machine perception, autonomous navigation, and pattern recognition. Common applications of MRO include mapping gas distributions, locating and detecting gas sources, and tracking gas plumes. Aerial Robot Olfaction (ARO) is a specialized branch of MRO that adapts these concepts to aerial robots, addressing the challenges of airborne gas sensing. This presentation highlights recent developments and results from ongoing research projects in MRO and ARO, with a focus on real-world deployment scenarios and the challenges encountered in practice. T2 - Drohnen in der Zerstörungsfreien Prüfung CY - Magdeburg, Germany DA - 26.11.2025 KW - Ground and Aerial robots KW - Gas distribution mapping KW - Gas source localization KW - Gas Tomography KW - Mobile Robotic Olfaction PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-648928 UR - https://www.ndt.net SP - 1 EP - 15 PB - DGZfP AN - OPUS4-64892 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 -