Analytische Chemie
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- Mobile Robot Olfaction (12) (entfernen)
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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.
Der Vortrag gibt Beispiele dafür, wie Drohnen sinnvoll im zivilen Bereich eingesetzt werden können. Insbesondere werden die Lokalisierung von Gasemissionsquellen und die Erstellung von Gasverteilungskarten vorgestellt.
Precise knowledge about the distribution of air pollutants is necessary to develop plausible occupational health measures. Combinatory systems, consisting of mobile robots and stationary sensors, can be effective solutions for the coverage of large measurement areas. However, further research is needed to fully understand their performance in comparison to traditional sensing strategies. Therefore, multiple sensor networks layouts will be set up in a simulation environment as well as in real industrial environments. Models for distribution mapping will be developed and evaluated to investigate the performance and opportunities of hybrid-mobility sensor networks for the task of distribution mapping.
Aerial Robot Olfaction @BAM
(2021)
Simulating a Gas Source Localization Algorithm with Gas Dispersion Produced by Recorded Outdoor Wind
(2022)
This presentation reports the use of the first gas dispersion simulator capable of generating large wind fluctuation, to test a modification to a gas source localization algorithm and study how the change affects it. Gas source localization at an outdoor environment is a challenging task mainly due to the complexity of the spreading gas caused by the unpredictable nature of constantly changing wind. Therefore, a novel use of outdoor wind in developing a gas source localization system by simulation will be shared. To consider the characteristic of sudden but large and unpredictable changes in wind direction, recorded outdoor wind was used to simulate a realistic outdoor gas dispersion which has been done for the first time. With the use of this simulator, a modification to a mobile robot-based gas source localization algorithm was evaluated. Multiple simulations of the modified and the original algorithm were done to study the effect of the tested modification. The results showed that a small difference in the algorithm can greatly impact the results. From this study, we consider the use of simulation consisting of the necessary traits to evaluate outdoor gas source localization, has the potential to accelerate the development of a reliable localization system.