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Verkehrsunfälle unter Beteiligung von Fahrzeugen mit alternativen Kraftstoffen wie LPG („Autogas“, Liquefied Petroleum Gas), CNG (Compressed Natural Gas, komprimiertes Erdgas) oder CGH2 (Compressed Gas Hydrogen, komprimierter Wasserstoff), bergen neue, komplexe Risiken für Passagiere, Einsatzkräfte und deren Umfeld. Im Rahmen des Projektes „CoFi-ABV“ beschäftigt sich die Bundesanstalt für Materialforschung und -prüfung (BAM) unter Berücksichtigung komplexer Brand- und Explosionsszenarien mit einer ganzheitlichen Betrachtung der Auswirkungen des unfallbedingten Versagens von Gasbehältern für alternative Kraftstoffe. Ein wichtiger Teil des Forschungsvorhabens umfasst Entwicklung, Aufbau und Validierung einer unbemannten Flugplattform (Unmanned Aerial Vehicle, UAV) zur Ferndetektion von Gaswolken. Für das sogenannte gassensitive Mini-UAV wird ein robuster Open-Path-Gasdetektor auf einer Sensorbewegungsplattform in Form eines modifizierten Kamera-Gimbals, integriert. Ziel ist es, ein leistungsfähiges und robustes Werkzeug zu entwickeln, welches Einsatzkräften im Falle eines Unfalls als Hilfe zur Abschätzung der Gefahr durch Gaswolken, ihrer Ausbreitung und der notwendigen Absperrbereiche zur Verfügung steht. Dieser Artikel ist der zweite der Reihe und legt, nach Projektvorstellung im ersten Teil, nun den Schwerpunkt auf das gassensitive Mini-UAV.
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.
BAM Federal Institute for Materials Research and Testing, in cooperation with the AirRobot GmbH & Co. KG company, has developed a flying remote-controlled measuring system. The system is capable of operating in a variety of scenarios of gas emissions, e.g. exhaust gas from chimneys, flue gas in a fire, gas emissions in the case of an accident of chemical or hazardous goods or in the case of a terrorist act involving toxic gases. Thus it can measure the gas concentration in the immediate vicinity of the object which causes the emission. A further stage of extension is to enhance the system for plume tracking and identification of sources of hazardous gases.
Aerial Robot Olfaction @BAM
(2021)
A set of equations is derived to estimate the 3D wind vector with a multirotor aircraft using the aircraft itself as a flying anemometer. Since the thrust component is required to compute the wind vector, the PWM signal controlling the motors of the aircraft is measured and a transfer function describing the relation between the PWM signal and the rotational speed of the motors is derived.
For several applications involving multirotor aircraft, it is crucial to know both the direction and speed of the ambient wind. In this paper, an approach to wind vector estimation based on an equilibrium of the principal forces acting on the aircraft is shown. As the thrust force generated by the rotors depends on their rotational speed, a sensor to measure this quantity is required. Two concepts for such a sensor are presented: One is based on tapping the signal carrying the speed setpoint for the motor controllers, the other one uses phototransistors placed underneath the rotor blades. While some complications were encountered with the first approach, the second yields accurate measurement data. This is shown by an experiment comparing the proposed speed sensor to a commercial non-contact tachometer.