TY - CONF A1 - Neumann, Patrick P. A1 - Hirschberger, Paul A1 - Baurzhan, Zhandos A1 - Tiebe, Carlo A1 - Hofmann, Michael A1 - Hüllmann, Dino A1 - Bartholmai, Matthias T1 - Indoor air quality monitoring using flying nanobots: Design and experimental study T2 - 2019 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) N2 - In this paper, we introduce a nano aerial robot swarm for Indoor Air Quality (IAQ) monitoring applications such as occupational health and safety of (industrial) workplaces. The robotic swarm is composed of nano Unmanned Aerial Vehicles (UAVs), based on the Crazyflie 2.0 quadrocopter, and small lightweight Metal Oxide (MOX) gas sensors for measuring the Total Volatile Organic Compound (TVOC), which is a measure for IAQ. An indoor localization and positioning system is used to estimate the absolute 3D position of the swarm similar to GPS. A test scenario was built up to validate and optimize the swarm for the intended applications. Besides calibration of the IAQ sensors, we performed experiments to investigate the influence of the rotor downwash on the gas measurements at different altitudes and compared them with stationary measurements. Moreover, we did a first evaluation of the gas distribution mapping performance. Based on this novel IAQ monitoring concept, new algorithms in the field of Mobile Robot Olfaction (MRO) are planned to be developed exploiting the abilities of an aerial robotic swarm. T2 - 2019 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) CY - Fukuoka, Japan DA - 26.05.2019 KW - Indoor air quality KW - Nano aerial robot KW - Aerial robot olfaction KW - Swarm KW - Gas detector PY - 2019 SN - 978-1-5386-8327-9 SN - 978-1-5386-8328-6 DO - https://doi.org/10.1109/ISOEN.2019.8823496 SP - 1 EP - 3 PB - IEEE AN - OPUS4-48920 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 - TY - CONF A1 - Neumann, Patrick P. A1 - Hüllmann, Dino A1 - Bartholmai, Matthias ED - Pastramă, D. Ş ED - Constantinescu, D. M. T1 - Concept of a gas-sensitive nano aerial robot swarm for indoor air quality monitoring T2 - 35th Danubia - Adria Symposium on Advances in Experimental Mechanics - Extended abstracts N2 - In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%. To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources. T2 - 35th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Sinaia, Romania DA - 25.09.2018 KW - Mobile Robot Olfaction KW - Swarm KW - Nano aerial robot KW - Gas sensing PY - 2018 SN - 978-606-23-0874-2 SP - 139 EP - 140 PB - PRINTECH CY - Bukarest AN - OPUS4-46137 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Hüllmann, Dino A1 - Bartholmai, Matthias A1 - Tiebe, Carlo T1 - Concept of a gas-sensitive nano aerial robot swarm for indoor air quality monitoring N2 - In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%. To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources. T2 - NetMon International training course - Low-cost Environmental Monitoring CY - BAM, Berlin, Germany DA - 09.04.2019 KW - Gas sensing KW - Mobile Robot Olfaction KW - Nano aerial robot KW - Swarm PY - 2019 AN - OPUS4-47799 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Hüllmann, Dino A1 - Bartholmai, Matthias A1 - Tiebe, Carlo A1 - Krentel, Daniel A1 - Kluge, Martin A1 - Kohlhoff, Harald A1 - Lilienthal, A. J. T1 - Gas Tomography Up In The Air! N2 - In this paper, we present an autonomous aerial robot to reconstruct tomographic 2D slices of gas plumes in outdoor environments. Our platform, the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS) combines a lightweight Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile octocopter. The TDLAS sensor provides integral gas concentration measurements but no information regarding the distance traveled by the laser diode's beam or the distribution of the gas along the optical path. We complemented the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from these integral concentration measurements. To allow for a rudimentary ground truth evaluation of the applied gas tomography algorithm, we set up a unique outdoor test environment based on two 3D ultrasonic anemometers and a distributed array of 10 infrared gas transmitters. We present first results showing the 2D plume reconstruction capabilities of the system under realistic conditions. T2 - NetMon International training course - Low-cost Environmental Monitoring CY - BAM, Berlin, Germany DA - 09.04.2019 KW - Aerial robot KW - Gas tomography KW - Plume KW - TDLAS PY - 2019 AN - OPUS4-47800 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hüllmann, Dino A1 - Neumann, Patrick P. A1 - Bartholmai, Matthias A1 - Tiebe, Carlo A1 - Paul, Niels A1 - Lilienthal, A. J. T1 - Wind Vector Estimation on Multirotor Aircraft N2 - An equation for wind vector estimation using a multirotor aircraft as a flying anemometer is shown. To compute the wind vector an estimate of the thrust of the aircraft is required, which is related to the rotational speed of the rotors. Hence, a sensing system for the rotational speed using phototransistors is presented. T2 - NetMon International training course - Low-cost Environmental Monitoring CY - BAM, Berlin, Germany DA - 09.04.2019 KW - Anemometer KW - Phototransistor KW - Thrust KW - Wind PY - 2019 AN - OPUS4-47801 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -