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 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 -