TY - CONF A1 - Neumann, Patrick P. A1 - Grotelüschen, Bjarne A1 - Bartholmai, Matthias A1 - Strangfeld, Christoph ED - Kossa, A. ED - Kiss, R. T1 - Towards Autonomous NDT Inspection: Setup and Validation of an Indoor Localization System N2 - Monitoring and maintenance of civil infrastructure are of great importance, as any undetected damage can cause high repair costs, unintended deadtime, or endanger structural integrity. The inspection of large concrete structures such as bridges and parking lots is particularly challenging and time-consuming. Traditional methods are mostly manual and involve mapping a grid of measurement lines to record the position of each measurement. Current semi-automated methods, on the other hand, use GPS or tachymeters for localization but still require trained personnel to operate. An entirely automated approach using mobile robots would be more cost- and time-efficient. While there have been developments in using GPS-enabled mobile robots for bridge inspection, the weak signal strength in indoor areas poses a challenge for the automated inspection of structures such as parking lots. This paper aims to develop a solution for the automated inspection of large indoor concrete structures by addressing the problem of robot localization in indoor spaces and the automated measurement of concrete cover and rebar detection. T2 - 39th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Siófok, Hungary DA - 26.09.2023 KW - NDT Inspection KW - Mobile Robot KW - Indoor Localization KW - Setup and Validation PY - 2023 SN - 978-963-421-927-9 SP - 88 EP - 89 PB - Hungarian Scientific Society of Mechanical Engineering (GTE) CY - Siófok, Hungary AN - OPUS4-58660 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Johann, Sergej A1 - Kohlhoff, Harald A1 - Neumann, Patrick P. T1 - Revisiting Environmental Sensing Nodes: Lessons Learned and Way Forward N2 - Setting up sensors for the purpose of environmental monitoring should be a matter of days, but often drags over weeks or even months, preventing scientists from doing real research. Additionally, the newly developed hardware and software solutions are often reinventing existing wheels. In this short paper, we revisit the design of our environmental sensing node that has been monitoring industrial areas over a span of two years. We share our findings and lessons learned. Based on this, we outline how a new generation of sensing node(s) can look like. T2 - SMSI 2023 Conference Sensor and Measurement Science International CY - Nuremberg, Germany DA - 08.05.2023 KW - Sensing node KW - Sensor network KW - Environmental monitoring KW - Low-cost KW - LoRaWAN PY - 2023 SN - 978-3-9819376-8-8 DO - https://doi.org/10.5162/SMSI2023/C5.1 SP - 173 EP - 174 PB - AMA Service GmbH CY - Wunstorf AN - OPUS4-57454 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Neumann, Patrick P. A1 - Hüllmann, Dino A1 - Winkler, Nicolas P. A1 - Lohrke, Heiko A1 - Lilienthal, A. J. ED - Lee, J. B. T1 - Outdoor Gas Plume Reconstructions: A Field Study with Aerial Tomography N2 - 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. T2 - 20th International Symposium on Olfaction and Electronic Nose CY - Grapevine, Texas, USA DA - 12.05.2024 KW - Aerial robot KW - TDLAS KW - Gas Tomography KW - Plume PY - 2024 SN - 979-8-3503-4865-1 SP - 1 EP - 3 PB - IEEE CY - USA AN - OPUS4-60107 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Winkler, Nicolas P. A1 - Neumann, Patrick P. A1 - Schaffernicht, Erik A1 - Lilienthal, Achim T1 - Gas Distribution Mapping With Radius-Based, Bi-directional Graph Neural Networks (RABI-GNN) N2 - Gas Distribution Mapping (GDM) is essential in monitoring hazardous environments, where uneven sampling and spatial sparsity of data present significant challenges. Traditional methods for GDM often fall short in accuracy and expressiveness. Modern learning-based approaches employing Convolutional Neural Networks (CNNs) require regular-sized input data, limiting their adaptability to irregular and sparse datasets typically encountered in GDM. This study addresses these shortcomings by showcasing Graph Neural Networks (GNNs) for learningbased GDM on irregular and spatially sparse sensor data. Our Radius-Based, Bi-Directionally connected GNN (RABI-GNN) was trained on a synthetic gas distribution dataset on which it outperforms our previous CNN-based model while overcoming its constraints. We demonstrate the flexibility of RABI-GNN by applying it to real-world data obtained in an industrial steel factory, highlighting promising opportunities for more accurate GDM models. T2 - International Symposium on Olfaction and Electronic Nose (ISOEN) CY - Grapevine, TX, USA DA - 12.05.2024 KW - Gas distribution mapping KW - Spatial interpolation KW - Graph neural networks KW - Mobile robot olfaction PY - 2024 SN - 979-8-3503-7053-9 SP - 1 EP - 3 PB - IEEE AN - OPUS4-60103 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lohrke, Heiko A1 - Kohlhoff, Harald A1 - Neumann, Patrick P. ED - Lee, J. B. T1 - Robotic Scanning Absorption Spectroscopy for Methane Leak Detection: the Virtual Gas Camera N2 - 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. T2 - 20th International Symposium on Olfaction and Electronic Nose CY - Grapevine, Texas, USA DA - 12.05.2024 KW - Mobile Robotic Olfaction KW - TDLAS KW - Gas Tomography KW - Gas Camera KW - Plume PY - 2024 SN - 979-8-3503-4865-1 SP - 1 EP - 3 PB - IEEE CY - USA AN - OPUS4-60109 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - A New Approach: Passive Smart Dust for Detection of Hazardous Substances N2 - Remote sensing of hazardous substances is a key task that can be achieved with the help of remotely operated platforms equipped with specific sensors. A huge variety of methods and used vehicles have been developed for different purposes in recent years. The term smart dust refers to a science fiction novel and develop shortly after into a research proposal at UC Berkley funded by DARPA. Subsequently, the topic gained attraction but was overall considered as to complex for the technologies available at that time. In the launched passive smart dust project, we shift to a simple “chemical intelligent” passive sensor particle on the ground combined a read-out active sensor attached to an Unmanned Aerial Vehicle (UAV). The reactive particle surface can be preadjusted in the lab for exact desired properties regarding certain reactions to hazardous substances. Moreover, the aimed interaction with the active sensor can be modified. Planed applications allow for different materials e.g., for short time measurement, being ecologically degradable, or weather stable for long time monitoring. T2 - 38th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Poros, Greece DA - 20.09.2022 KW - Smart Dust KW - Drone KW - Remote Detection KW - Hazardous substances PY - 2022 SP - 1 EP - 2 CY - Athens, Greece AN - OPUS4-55925 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - Drone-based Localization of Hazardous Chemicals by Passive Smart Dust N2 - We introduce a passive smart dust concept as a novel solution for environmental monitoring. Utilizing chemical reagents like colorimetric indicators and other chemosensors, these particles detect varying environmental conditions. We developed paper-based sensors that are both cost-effective and eco-friendly. In practical tests, these sensors, dispersed over a designated area, successfully identified hazardous substances by changing their color when exposed to acids or bases. This color change was remotely detectable using a drone-mounted color camera. The data thus obtained was processed through specialized software, accurately pinpointing areas of contamination. This method proves the efficacy and scalability of passive smart dust technology for real-time, environmentally sustainable remote sensing of hazardous materials T2 - 2024 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) CY - Grapevine, Texas, USA DA - 12.05.2024 KW - Indicator KW - Passive Smart Dust KW - Colorimetric Sensor KW - Drone KW - Cellulose KW - Environmental Monitoring KW - Confetti KW - Hazard Detection PY - 2024 SN - 979-8-3503-7053-9 VL - 1 SP - 1 EP - 3 PB - IEEE CY - Piscataway, NJ 08855-1331 USA AN - OPUS4-60176 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Nerger, Tino A1 - Neumann, Patrick P. A1 - Weller, Michael G. T1 - Passive Smart Dust a versatile low-cost sensor platform N2 - Coated cellulose particles as colourimetric passive sensors that are detected by the optical camera system of a drone. In this way, hazardous substances, e.g. acids, can be detected from a safe distance in a cost-effective and environmentally friendly way. N2 - Beschichtete Zellulose Partikel als kolorimetrische passive Sensoren, die mittels optische Kamerasystem einer Drohne erfasst werden. Somit können Gefahrenstoffe, in ersten Versuchen zB Säuren aus sicherer Entfernung, kostengünstig und umweltverträglich detektiert werden. T2 - SMSI 2023 Sensor and Measurement Science International CY - Nuremberg, Germany DA - 08.05.2023 KW - Passive Smart Dust KW - Drone KW - Colorimetric sensor particles KW - Remote detection PY - 2023 DO - https://doi.org/10.5162/SMSI2023/C5.3 SP - 1 EP - 2 AN - OPUS4-57527 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Johann, Sergej A1 - Stührenberg, Jan A1 - Tandon, Aditya A1 - Dragos, Kosmas A1 - Bartholmai, Matthias A1 - Strangfeld, Christoph A1 - Smarsly, Kay T1 - Implementation and validation of robot-enabled embedded sensors for structural health monitoring N2 - In the past decades, structural health monitoring (SHM) has matured into a viable supplement to regular inspections, facilitating the execution of repair and maintenance work in the early stages of structural damage. With the advent of wireless technologies and advancements in information and communication technologies, civil infrastructure has been increasingly instrumented with wireless sensor nodes to record, analyze, and communicate data relevant to SHM. A promising method for SHM is to embed sensors directly into concrete for recording SHM data from inside structural elements. In this paper, a sensor system for embedment into concrete is proposed, able to assess SHM data recorded from concrete. Power is supplied to the sensors on-demand by quadruped robots, which also collect the SHM data via radio-frequency identification (RFID), providing an automated and efficient SHM process. In laboratory experiments, the capability of the sensor system of automatically collecting the SHM data using quadruped robots is validated. In summary, the integration of RFID technology and robot-based inspection presented in this study demonstrates a vital approach to evolve current SHM practices towards more digitalized and automated SHM. T2 - 11th European Workshop On Structural Health Monitoring CY - Potsdam, Germany DA - 10.06.2024 KW - Structural health monitoring KW - RFID-based sensors KW - Smart sensors KW - Embedded sensors KW - Legged robots KW - Quadruped robots PY - 2024 SP - 1 EP - 8 AN - OPUS4-60335 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 -