Filtern
Dokumenttyp
- Beitrag zu einem Tagungsband (5)
- Vortrag (2)
- Posterpräsentation (2)
Schlagworte
- Gas Tomography (5)
- Mobile Robotic Olfaction (4)
- TDLAS (4)
- Aerial robot (2)
- Gas tomography (2)
- Greenhouse Gas Emissions (2)
- Methane (2)
- Plume (2)
- Remote Gas Sensing (2)
- Robot (2)
Organisationseinheit der BAM
This paper outlines significant advancements in our previously developed aerial gas tomography system, now optimized to reconstruct 2D tomographic slices of gas plumes with enhanced precision in outdoor environments. The core of our system is an aerial robot equipped with a custom-built 3-axis aerial gimbal, a Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor for CH4 measurements, a laser rangefinder, and a wide-angle camera, combined with a state-of-the-art gas tomography algorithm. In real-world experiments, we sent the aerial robot along gate-shaped flight patterns over a semi-controlled environment with a static-like gas plume, providing a welldefined ground truth for system evaluation. The reconstructed cross-sectional 2D images closely matched the known ground truth concentration, confirming the system’s high accuracy and reliability. The demonstrated system’s capabilities open doors for potential applications in environmental monitoring and industrial safety, though further testing is planned to ascertain the system’s operational boundaries fully.
This seminar presents the key research activities of ARO Lab@BAM, focusing on five main areas:
• Learning-based Gas Distribution Mapping utilizes machine learning to accurately model and predict spatial gas concentrations, enhancing environmental monitoring and safety.
• Mimose-A develops autonomous systems using artificial intelligence to enable the early detection of leaks in industrial environments.
• AGATO (Gastomography) introduces a novel robotic system for high-resolution gas distribution mapping.
• Passive Smart Dust detects chemically hazardous substances using drones equipped to distribute and detect particles carrying selective dyes, enabling rapid and reliable monitoring without complex components.
• HyAirLogic Lab advances hydrogen (H₂) research by testing the entire value chain in various Berlin-Brandenburg quarters, addressing technological challenges, public acceptance, and sustainable energy solutions for H₂-cargo drones.
This paper explores combining a gimbal-mounted tunable diode laser absorption spectroscopy (TDLAS) sensor and a video camera to create a virtual gas camera for methane leak detection. This provides a low-to-zero-cost extension of typical TDLAS gas tomography systems. A prototype setup mounted on a ground robot is evaluated. Results acquired using a simulated methane leak show the feasibility of the virtual gas camera, accurately detecting methane leaks by overlaying concentrations onto a visual image. While the acquisition time is significantly longer than for traditional gas cameras, potential enhancements are discussed. The study concludes that the virtual gas camera is feasible and useful, despite its longer acquisition time. It serves as a valuable software-only addition to typical TDLAS gas tomography systems, offering quickly-available on-site data augmentation for visual leak assessment at low-to-zero cost.
Ziel des FuE-Vorhabens ist die Entwicklung, Aufbau und Validierung eines gasto-mographischen Messsystems basierend auf stationärer und mobiler Sensorik zum Emissionsmonitoring in kommunalen Kläranlagen. Die Gastomographie basiert hierbei im Wesentlichen auf, aus unterschiedlichen Sichtwinkeln aufgenommenen, integralen Konzentrationsmessungen, anhand derer eine Rekonstruktion der Gasverteilung erfolgt. Das FuE-Projekt kombiniert hierfür stationäre Sensornetzwerke mit luftgestützten und bodengebundenen Robotersystemen in einem System. Letztere werden mit Reflektoren und/oder Gasdetektoren ausgestattet. Hierfür werden Open-Path-Gasmesstechnik basierend auf Tunable Diode Laser Ab-sorption Spectroscopy (TDLAS, primär CH4 in ppm·m) und In-situ-Gassensorik (CH4, ppm) auf Basis von z.B. Infrarot eingesetzt. Dies sind zwei komplementäre Methoden der Gasmessung: Die In-situ-Gassensorik ermöglicht Punktmessungen, wohingegen TDLAS-Sensoren Gaskonzentrationen integral über offene Messstre-cken von bis zu 60 m gegen Oberflächen messen. Die In-situ-Gassensorik wird für Referenzmessungen und ggf. zur Erhöhung der Rekonstruktionsqualität zum Ein-satz kommen. Die wesentlichen Neuheiten des Projekts sind:
• 2D-Gastomographie auf Basis eines mit TDLAS-basierter Open-Path-Gasmesstechnik und Reflektoren ausgestatteten heterogenen Messsystems.
• CT-basierte Rekonstruktionsalgorithmen, adaptiert an die komplexen Rahmenbedingungen.
• Validierung des Messsystems anhand realer Messungen auf Kläranlagen.
Robotic Measurement System Concept for Greenhouse Gas Tomography in Wastewater Treatment Plants
(2023)
This paper introduces a conceptual framework for a robotic greenhouse gas (GHG) measurement system designed for wastewater treatment plants (WWTPs). The emphasis is on accurate gas tomography measurement of emissions, crucial for national emission assessments. The proposed system is movable, semi-autonomous, and employs a combination of ground and air robots equipped with integral remote gas sensors and in-situ sensors. Employing a two/two configuration ensures comprehensive coverage of WWTPs, overcoming obstacles. The system concept lays the foundation for future implementation and evaluation, addressing the need for enhanced understanding of GHG emissions from WWTPs.
Methane emissions are a significant environmental and safety concern, yet many gas tomography systems intended to measure them require manual alignment, reliable high-bandwidth links, or fiducials. We present a lightweight, fully autonomous framework enabling line-of-sight inter-robot Tunable Diode Laser Absorption Spectroscopy (TDLAS) measurements without such constraints. A sensor robot equipped with a gimbal-mounted TDLAS unit tracks a reflector robot bearing an illuminated, color-controllable target. Coarse localization is achieved via RTK-GNSS, with vision-based fine tracking and passive time synchronization handled onboard. The system, based on off-the-shelf Pixhawk controllers and ArduPilot firmware, was validated in a 15m × 7m outdoor trial. Despite GNSS inaccuracies and deliberate occlusion by a methane-filled bag, the system retained lock, recovered from visual loss in under one second, and captured a 2800 ppm·m plume signature. These results demonstrate robust, scalable methane sensing for mobile gas tomography or standalone leak detection. Core components are released open-source to support future deployment.
Robotic Measurement System Concept for Greenhouse Gas Tomography in Wastewater Treatment Plants
(2023)
This paper introduces a conceptual framework for a greenhouse gas (GHG) measurement system designed for wastewater treatment plants (WWTPs). The emphasis is on accurate gas tomography measurements of emissions, crucial for national emission assessments. The proposed system is movable, semi-autonomous, and employs a combination of ground and air robots equipped with integral remote gas sensors and in-situ sensors. The proposed two/two configuration ensures comprehensive coverage of WWTPs, overcoming obstacles. The system concept lays the foundation for future implementation and evaluation, addressing the need for enhanced understanding of GHG emissions from WWTPs.
Methane emissions are a significant environmental and safety concern, yet many gas tomography systems intended to measure them require manual alignment, reliable high-bandwidth links, or fiducials. We present a lightweight, fully autonomous framework enabling line-of-sight inter-robot Tunable Diode Laser Absorption Spectroscopy (TDLAS) measurements without such constraints. A sensor robot equipped with a gimbal-mounted TDLAS unit tracks a reflector robot bearing an illuminated, color-controllable target. Coarse localization is achieved via RTK-GNSS, with vision-based fine tracking and passive time synchronization handled onboard. The system, based on off-the-shelf Pixhawk controllers and ArduPilot firmware, was validated in a 15m × 7m outdoor trial. Despite GNSS inaccuracies and deliberate occlusion by a methane-filled bag, the system retained lock, recovered from visual loss in under one second, and captured a 2800 ppm·m plume signature. These results demonstrate robust, scalable methane sensing for mobile gas tomography or standalone leak detection. Core components are released open-source to support future deployment.
In recent decades, robotics, particularly in environmental monitoring, has made significant advances. Robots of various forms and sizes have become essential tools for data collection in environmental research. Mobile Robot Olfaction (MRO) involves mobile robots equipped with gas sensors and requires the integration of multiple disciplines, including signal processing, machine perception, autonomous navigation, and pattern recognition. Common applications of MRO include mapping gas distributions, locating and detecting gas sources, and tracking gas plumes. Aerial Robot Olfaction (ARO) is a specialized branch of MRO that adapts these concepts to aerial robots, addressing the challenges of airborne gas sensing.
This presentation highlights recent developments and results from ongoing research projects in MRO and ARO, with a focus on real-world deployment scenarios and the challenges encountered in practice.
