TY - JOUR A1 - Neumann, Patrick P. A1 - Hüllmann, Dino A1 - Bartholmai, Matthias ED - Pastramă, Ş. D. ED - Constantinescu, D. M. T1 - Concept of a gas-sensitive nano aerial robot swarm for indoor air quality monitoring JF - Materials Today: Proceedings N2 - In this paper, we introduce a nano aerial robot swarm for indoor air quality monitoring applications such as occupational health and safety of (industrial) workplaces. The concept combines a robotic swarm composing of nano Unmanned Aerial Vehicles (nano UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight metal oxide gas sensors for measuring the Total Volatile Organic Compound (TVOC) in ppb and estimating the eCO2 (equivalent calculated carbon-dioxide) concentration in ppm. TVOC is a measure for the indoor air quality. An indoor localization and positioning system will be used to estimate the absolute 3D position of the swarm like GPS. Based on this novel indoor air quality monitoring concept, the development and validation of new algorithms in the field of Mobile Robot Olfaction (MRO) are planned, namely gas source localization and gas distribution mapping. A test scenario will be built up to validate and optimize the gas-sensitive nano aerial robot swarm for the intended applications. T2 - 35th Danubia Adria Symposium on Advances in Experimental Mechanics CY - Sinaia, Romania DA - 25.09.2018 KW - Nano aerial robot KW - UAV KW - Swarm KW - Indoor air quality KW - Monitoring KW - Concept PY - 2019 DO - https://doi.org/10.1016/j.matpr.2019.03.151 SN - 2214-7853 VL - 12 IS - 2 SP - 470 EP - 473 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-48055 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hüllmann, Dino A1 - Neumann, Patrick P. A1 - Bartholmai, Matthias T1 - Wind Vector Estimation on Multirotor Aircraft N2 - Small unmanned aircraft (UA) are used increasingly as flying sensor platforms. Amongst other things they are used for environmental monitoring, for example gas distribution mapping. Sometimes, these applications require knowledge of the ambient wind field, which can be measured by additional devices like anemometers. In general, it would be interesting to avoid such additional apparatuses. One way to achieve this is to estimate the wind vector, that is both the wind direction and speed, from the state variables of the UA. T2 - IEEE Sensors 2018 CY - New Delhi, India DA - 28.10.2018 KW - UAV KW - Wind vector KW - Estimation KW - Multirotor aircraft PY - 2018 AN - OPUS4-46479 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -