TY - CONF A1 - Winkler, Nicolas P. A1 - Neumann, Patrick P. A1 - Hüllmann, Dino A1 - Kohlhoff, Harald A1 - Bartholmai, Matthias A1 - Bennetts, V. H. A1 - Lilienthal, A. J. T1 - Remote Gas Sensing with Multicopter-Platforms N2 - This presentation gives an introduction to the gas-sensitive aerial robots developed at BAM, including various application examples in the field of mobile robot olfaction: gas source localization and gas distribution mapping. T2 - Zweites Innovationsforum "Autonome, mobile Dienste; Services für Mobilität" CY - Berlin, Germany DA - 04.06.2019 KW - Tunable Diode Laser Absorption Spectroscopy (TDLAS); UAV-REGAS KW - Localization of gas sources KW - Mobile Robot Olfaction KW - Nano UAV Swarm KW - Tomographic reconstruction of gas plumes PY - 2019 UR - http://modisem.de/files/Ereignisse/2019-06/Innovationsforum_Downloads/IF2_2019_Tagungsband_WEB.pdf SN - 978-3-942709-22-4 N1 - Tagungsband auf Deutsch, Beitrag auf Englisch. VL - 2019 SP - 24 EP - 34 AN - OPUS4-48699 LA - mul AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 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 - 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 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 - Hüllmann, Dino A1 - Neumann, Patrick P. A1 - Scheuschner, Nils A1 - Bartholmai, Matthias A1 - Lilienthal, A.J. T1 - Experimental Validation of the Cone-Shaped Remote Gas Sensor Model N2 - Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or hardly accessible areas. A challenging task, however, is the generation of threedimensional distribution maps from these gas measurements. Suitable reconstruction algorithms can be adapted, for instance, from the field of computed tomography (CT), but both their performance and strategies for selecting optimal measuring poses must be evaluated. For this purpose simulations are used, since, in contrast to field tests, they allow repeatable conditions. Although several simulation tools exist, they lack realistic models of remote gas sensors. Recently, we introduced a model for a Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor taking into account the conical shape of its laser beam. However, the novel model has not yet been validated with experiments. In this paper, we compare our model with a real sensor device and show that the assumptions made hold. T2 - IEEE Sensors 2019 CY - Montreal, Canada DA - 27.10.2019 KW - Remote gas sensor model KW - TDLAS KW - Gas dispersion simulation PY - 2019 SN - 978-1-7281-1634-1 SP - 104 EP - 107 PB - IEEE AN - OPUS4-49548 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -