TY - CONF A1 - Gawlitza, Kornelia A1 - Bartelmeß, Jürgen A1 - Bartholmai, Matthias A1 - Neumann, Patrick P. A1 - Johann, Sergej A1 - Tiebe, Carlo A1 - Banach, Ulrich A1 - Noske, Reinhard A1 - Rurack, Knut T1 - Fluorescence sensor for the long-term monitoring of gaseous ammonia N2 - Ammonia and its reaction products can cause considerable damage of human health and ecosystems, increasing the necessity for reliable and reversible sensors to monitor traces of gaseous ammonia in ambient air directly on-site or in the field. Although various types of gas sensors are available, fluorescence sensors have gained importance due to advantages such as high sensitivity and facile miniaturization. Here, we present the development of a sensor material for the detection of gaseous ammonia in the lower ppm to ppb range by incorporation of a fluorescent dye, which shows reversible fluorescence modulations as a function of analyte concentration, into a polymer matrix to ensure the accumulation of ammonia. A gas standard generator producing standard gas mixtures, which comply with the metrological traceability in the desired environmentally relevant measurement range, was used to calibrate the optical sensor system. To integrate the sensor material into a mobile device, a prototype of a hand-held instrument was developed, enabling straightforward data acquisition over a long period. T2 - Colloquium of Optical Spectrometry (COSP) 2017 CY - Berlin, Germany DA - 27.11.2017 KW - Ammonia gas sensor KW - Fluorescence KW - Air quality monitoring KW - Standard gas generator KW - Miniaturized sensor device PY - 2017 AN - OPUS4-43143 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Johann, Sergej A1 - Bartholmai, Matthias A1 - Neumann, Patrick P. A1 - Tiebe, Carlo A1 - Gawlitza, Kornelia A1 - Bartelmeß, Jürgen T1 - Adaptable multi-sensor device for gas detection N2 - Innovation is the catalyst for the technology of the future. It is important to develop new and better technologies that can continuously monitor the environmental impact, e.g., for air quality control or emission detection. In the recently at BAM developed Universal Pump Sensor Control (UPSC3) module, different components and sensors are fused. The combination of the individual components makes the UPSC3 module an excellent monitoring and reference system for the development and characterization of gas specific sensors. Measurements over long periods are possible, for mixed gas loads or for certain gas measurements. The system is part of a mobile sensor network of several sensor units, which can also be used as standalone systems. The motivation and objective of this research is to develop gas sensors based on fluorescence detection with range of ppm / ppb. For this task a reference system is required, which contains volatile organic compound (VOC) sensors for reference data from different scenarios. The integrated multi-sensor unit can measure different gases through the integrated 3-fold VOC sensor, which can be adapted to the addressed scenario. . The system-integrated flow control, with pump and flow sensor, allows the gas molecules to be transported directly to the VOC sensor. The entire measurement is permanently stored on an integrated memory card. If the previously determined limit range is exceeded, an alarm is generated. The system is an important tool towards further developments in the field of gas sensors and is primarily used for the validation of chemically based gas sensors. T2 - Colloquium of Optical Spectrometry (COSP) 2017 CY - Berlin, Germany DA - 27.11.2017 KW - Gas detection KW - Multi sensor device KW - Pump control KW - VOC PY - 2017 AN - OPUS4-43193 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Johann, Sergej A1 - Tiebe, Carlo A1 - Gawlitza, Kornelia A1 - Bartelmeß, Jürgen A1 - Bartholmai, Matthias A1 - Hüllmann, Dino A1 - Krentel, Daniel A1 - Kluge, Martin A1 - Kohlhoff, Harald A1 - Lilienthal, A.J. T1 - Airborne Remote Gas Sensing and Mapping N2 - Leaking methane (CH4) from infrastructures, such as pipelines and landfills, is critical for the environment but can also pose a safety risk. To enable a fast detection and localization of these kind of leaks, we developed a novel robotic platform for aerial remote gas sensing. Spectroscopic measurement methods for remote sensing of selected gases lend themselves for use on mini-copters, which offer a number of advantages for inspection and surveillance over traditional methods. No direct contact with the target gas is needed and thus the influence of the aerial platform on the measured gas plume can be kept to a minimum. This allows to overcome one of the major issues with gas-sensitive mini-copters. On the other hand, remote gas sensors, most prominently Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensors have been too bulky given the payload and energy restrictions of mini-copters. Here, we present the Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), which combines a novel lightweight TDLAS sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile hexacopter. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO). It enables tomographic reconstruction of gas plumes and a localization of gas sources. We also present first results showing its performance under realistic conditions. T2 - Colloquium of Optical Spectrometry (COSP) 2017 CY - Berlin, Germany DA - 27.11.2017 KW - Tunable Diode Laser Absorption Spectroscopy (TDLAS) KW - UAV-REGAS KW - Mobile Robot Olfaction KW - Tomographic reconstruction of gas plumes KW - Localization of gas sources PY - 2017 AN - OPUS4-43204 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Kohlhoff, Harald A1 - Hüllmann, Dino A1 - Lilienthal, A.J. A1 - Kluge, Martin T1 - Bringing Mobile Robot Olfaction to the Next Dimension – UAV-based Remote Sensing of Gas Clouds and Source Localization N2 - This presentation introduces a novel robotic platform for aerial remote gas sensing. Spectroscopic measurement methods for remote sensing of selected gases lend themselves for use on mini-copters, which offer a number of advantages for inspection and surveillance. No direct contact with the target gas is needed and thus the influence of the aerial platform on the measured gas plume can be kept to a minimum. This allows to overcome one of the major issues with gas-sensitive mini-copters. On the other hand, remote gas sensors, most prominently Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensors have been too bulky given the payload and energy restrictions of mini-copters. Here, we introduce and present the Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), which combines a novel lightweight TDLAS sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile hexacopter. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO). It enables tomographic reconstruction of gas plumes and a localization of gas sources. We also present first results showing the gas sensing and aiming capabilities under realistic conditions. T2 - IEEE International Conference on Robotics and Automation (ICRA) CY - Singapore DA - 29.05.2017 KW - Tunable Diode Laser Absorption Spectroscopy (TDLAS) KW - 3-axis gimbal KW - Mobile Robot Olfaction KW - Tomographic reconstruction of gas plumes KW - Localization of gas sources KW - Aerial platform PY - 2017 AN - OPUS4-40547 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bennetts, V.H. A1 - Neumann, Patrick P. A1 - Kucner, T.P. A1 - Schaffernicht, E. A1 - Fan, H. A1 - Lilienthal, A.J. T1 - Probabilistic air flow modelling using turbulent and laminar characteristics for ground and aerial robots N2 - For mobile robots that operate in complex, uncontrolled environments, estimating air flow models can be of great importance. Aerial robots use air flow models to plan optimal navigation paths and to avoid turbulence-ridden areas. Search and rescue platforms use air flow models to infer the location of gas leaks. Environmental monitoring robots enrich pollution distribution maps by integrating the information conveyed by an air flow model. In this paper, we present an air flow modelling algorithm that uses wind data collected at a sparse number of locations to estimate joint probability distributions over wind speed and direction at given query locations. The algorithm uses a novel extrapolation approach that models the air flow as a linear combination of laminar and turbulent components. We evaluated the prediction capabilities of our algorithm with data collected with an aerial robot during several exploration runs. The results show that our algorithm has a high degree of stability with respect to parameter selection while outperforming conventional extrapolation approaches. In addition, we applied our proposed approach in an industrial application, where the characterization of a ventilation system is supported by a ground mobile robot. We compared multiple air flow maps recorded over several months by estimating stability maps using the Kullback-Leibler divergence between the distributions. The results show that, despite local differences, similar air flow patterns prevail over time. Moreover, we corroborated the validity of our results with knowledge from human experts. T2 - IEEE International Conference on Robotics and Automation (ICRA) CY - Singapore DA - 29.05.2017 KW - Mapping KW - Field robots KW - Environment monitoring and management KW - Aerial systems KW - Perception and autonomy PY - 2017 AN - OPUS4-40549 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -