TY - JOUR A1 - Neumann, Patrick P. A1 - Bennetts, V.H. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias A1 - Schiller, J.H. T1 - Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms N2 - Gas source localization (GSL) with mobile robots is a challenging task due to the unpredictable nature of gas dispersion, the limitations of the currents sensing technologies, and the mobility constraints of ground-based robots. This work proposes an integral solution for the GSL task, including source declaration. We present a novel pseudo-gradient-based plume tracking algorithm and a particle filter-based source declaration approach, and apply it on a gas-sensitive micro-drone. We compare the performance of the proposed system in simulations and real-world experiments against two commonly used tracking algorithms adapted for aerial exploration missions. KW - Autonomous micro UAV KW - Chemical and wind sensing KW - Gas source localization KW - Particle filter PY - 2013 U6 - https://doi.org/10.1080/01691864.2013.779052 SN - 0169-1864 SP - 725 EP - 738 PB - VNU Sciences Pr. CY - Utrecht AN - OPUS4-28010 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bennetts, V.H. A1 - Lilienthal, A.J. A1 - Neumann, Patrick P. A1 - Trincavelli, M. T1 - Mobile robots for localizing gas emission sources on landfill sites: is bio-inspiration the way to go? N2 - Roboticists often take inspiration from animals for designing sensors, actuators or algorithms that control the behaviour of robots. Bio-inspiration is motivated with the uncanny ability of animals to solve complex tasks like recognizing and manipulating objects, walking on uneven terrains, or navigating to the source of an odour plume. In particular the task of tracking an odour plume up to its source has nearly exclusively been addressed using biologically inspired algorithms and robots have been developed, for example, to mimic the behaviour of moths, dungbeetles, or lobsters. In this paper we argue that biomimetic approaches to gas source localization are of limited use, primarily because animals differ fundamentally in their sensing and actuation capabilities from state-of-the-art gas-sensitive mobile robots. To support our claim, we compare actuation and chemical sensing available to mobile robots to the corresponding capabilities of moths. We further characterize airflow and chemosensor measurements obtained with three different robot platforms (two wheeled robots and one flying micro drone) in four prototypical environments and show that the assumption of a constant and unidirectional airflow, which is at the basis of many gas source localization approaches, is usually far from being valid. This analysis should help to identify how underlying principles, which govern the gas source tracking behaviour of animals, can be usefully 'translated' into gas source localization approaches that fully take into account the capabilities of mobile robots. We also describe the requirements for a reference application, monitoring of gas emissions at landfill sites with mobile robots, and discuss an engineered gas source localization approach based on statistics as an alternative to biologically-inspired algorithms. KW - Mobile robotics KW - Mobile robot olfaction KW - Biologically inspired robots KW - Landfill surveillance PY - 2011 UR - http://journal.frontiersin.org/Journal/10.3389/fneng.2011.00020/full U6 - https://doi.org/10.3389/fneng.2011.00020 SN - 1662-6443 SP - 1 EP - 14 PB - Frontiers Research Foundation CY - Lausanne AN - OPUS4-25037 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Neumann, Patrick P. A1 - Asadi, S. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias A1 - Schiller, J.H. T1 - Autonomous gas-sensitive microdrone - wind vector estimation and gas distribution mapping N2 - This article presents the development and validation of an autonomous, gas sensitive microdrone that is capable of estimating the wind vector in real time using only the onboard control unit of the microdrone and performing gas distribution mapping (DM). Two different sampling approaches are suggested to address this problem. On the one hand, a predefined trajectory is used to explore the target area with the microdrone in a real-world gas DM experiment. As an alternative sampling approach, we introduce an adaptive strategy that suggests next sampling points based on an artificial potential field (APF). Initial results in real-world experiments demonstrate the capability of the proposed adaptive sampling strategy for gas DM and its use for gas source localization. KW - Anemometric sensor KW - Autonomous micro UAV KW - Chemical sensing KW - Gas distribution modelling KW - Gas source localization KW - Gas sensors KW - Mobile sensing system KW - Quadrocopter KW - Sensor planning KW - Artificial potential field PY - 2012 U6 - https://doi.org/10.1109/MRA.2012.2184671 SN - 1070-9932 VL - 19 IS - 1 SP - 50 EP - 61 PB - IEEE CY - New York, NY, USA AN - OPUS4-25773 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Neumann, Patrick P. A1 - Asadi, S. A1 - Hernandez Bennetts, V. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias T1 - Monitoring of CCS areas using micro unmanned aerial vehicles (MUAVs) N2 - Carbon capture & storage (CCS) is one of the most promising technologies for greenhouse gas (GHG) management. However, an unsolved issue of CCS is the development of appropriate long-term monitoring systems for leak detection of the stored CO2. To complement already existing monitoring infrastructure for CO2 storage areas, and to increase the granularity of gas concentration measurements, a quickly deployable, mobile measurement device is needed. In this paper, we present an autonomous gas-sensitive micro-drone, which can be used to monitor GHG emissions, more specifically, CO2. Two different measurement strategies are proposed to address this task. First, the use of predefined sensing trajectories is evaluated for the task of gas distribution mapping using the micro-drone. Alternatively, we present an adaptive strategy, which suggests sampling points based on an artificial potential field (APF). The results of real-world experiments demonstrate the feasibility of using gas-sensitive micro-drones for GHG monitoring missions. Thus, we suggest a multi-layered surveillance system for CO2 storage areas. T2 - GHGT 11 - Greenhouse gas control technologies conference CY - Kyoto, Japan DA - 18.11.2012 KW - Gas-sensitive micro-drone KW - Gas distribution mapping KW - Sensor planning KW - Artificial potential field KW - CCS PY - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-289119 SN - 1876-6102 VL - 37 SP - 4182 EP - 4190 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-28911 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Neumann, Patrick P. A1 - Schnürmacher, M. A1 - Bennetts, V.H. A1 - Lilienthal, A.J. A1 - Bartholmai, Matthias A1 - Schiller, J.H. T1 - A probabilistic gas patch path prediction approach for airborne gas source localization in non-uniform wind fields N2 - In this paper, we show that a micro unmanned aerial vehicle (UAV) equipped with commercially available gas sensors can address environmental monitoring and gas source localization (GSL) tasks. To account for the challenges of gas sensing under real-world conditions, we present a probabilistic approach to GSL that is based on a particle filter (PF). Simulation and real-world experiments demonstrate the suitability of this algorithm for micro UAV platforms. KW - Autonomous micro UAV KW - Chemical and wind sensing KW - Gas source localization KW - Particle filter PY - 2014 U6 - https://doi.org/10.1166/sl.2014.3168 SN - 1546-198X SN - 1546-1971 VL - 12 IS - 6/7 SP - 1113 EP - 1118 PB - American Scientific Publishers (ASP) CY - Stevenson Ranch, CA, USA AN - OPUS4-31525 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Winkler, Nicolas P. A1 - Neumann, Patrick P. A1 - Säämänen, A. A1 - Schaffernicht, E. A1 - Lilienthal, A. J. ED - Zemčík, R. ED - Krystek, J. T1 - High-quality meets low-cost: Approaches for hybrid-mobility sensor networks N2 - Air pollution within industrial scenarios is a major risk for workers, which is why detailed knowledge about the dispersion of dusts and gases is necessary. This paper introduces a system combining stationary low-cost and high-quality sensors, carried by ground robots and unmanned aerial vehicles. Based on these dense sampling capabilities, detailed distribution maps of dusts and gases will be created. This system enables various research opportunities, especially on the fields of distribution mapping and sensor planning. Standard approaches for distribution mapping can be enhanced with knowledge about the environment’s characteristics, while the effectiveness of new approaches, utilizing neural networks, can be further investigated. The influence of different sensor network setups on the predictive quality of distribution algorithms will be researched and metrics for the quantification of a sensor network’s quality will be investigated. T2 - 36th Danubia-Adria Symposium on Advances in Experimental Mechanics CY - Pilsen, Czech Republic DA - 24.09.2019 KW - Mobile robot olfaction KW - Air quality monitoring KW - Wireless sensor network KW - Gas distribution mapping KW - Occupational health PY - 2020 U6 - https://doi.org/10.1016/j.matpr.2020.05.799 VL - 32 SP - 250 EP - 253 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-51108 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Neumann, Patrick P. A1 - Kohlhoff, Harald A1 - Hüllmann, Dino A1 - Krentel, Daniel A1 - Kluge, Martin A1 - Dzierliński, M. A1 - Lilienthal, A. J. A1 - Bartholmai, Matthias T1 - Aerial-based gas tomography – from single beams to complex gas distributions N2 - In this paper, we present and validate the concept of an autonomous aerial robot to reconstruct tomographic 2D slices of gas plumes in outdoor environments. Our platform, the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), combines a lightweight Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor with a 3-axis aerial stabilization gimbal for aiming at a versatile octocopter. While the TDLAS sensor provides integral gas concentration measurements, it does not measure the distance traveled by the laser diode’s beam nor the distribution of gas along the optical path. Thus, we complement the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from a set of integral concentration measurements. To allow for a fundamental ground truth evaluation of the applied gas tomography algorithm, we set up a unique outdoor test environment based on two 3D ultrasonic anemometers and a distributed array of 10 infrared gas transmitters. We present results showing its performance characteristics and 2D plume reconstruction capabilities under realistic conditions. 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). KW - Aerial robot olfaction KW - Mobile robot olfaction KW - Gas tomography KW - TDLAS KW - Plume PY - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-487843 SP - 1 EP - 16 PB - Taylor & Francis CY - London AN - OPUS4-48784 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bennetts, V.H. A1 - Kucner, T.P. A1 - Schaffernicht, E. A1 - Neumann, Patrick P. 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 U6 - https://doi.org/10.1109/LRA.2017.2661803 SN - 2377-3766 VL - 2 IS - 2 SP - 1117 EP - 1123 PB - IEEE AN - OPUS4-39218 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hüllmann, Dino A1 - Paul, Niels A1 - Kohlhoff, Harald A1 - Neumann, Patrick P. A1 - Lilienthal, A. J. ED - Eberhardsteiner, J. ED - Růžička, M. ED - Cosmi, F. T1 - Measuring rotor speed for wind vector estimation on multirotor aircraft N2 - 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. T2 - 34th Danubia Adria Symposium on Advances in Experimental Mechanics CY - Trieste, Italy DA - 19.09.2017 KW - Wind vector estimation KW - Rotor speed KW - UAV KW - Tachometer PY - 2018 UR - https://www.sciencedirect.com/science/article/pii/S2214785318321114 U6 - https://doi.org/10.1016/j.matpr.2018.08.139 SN - 2214-7853 VL - 5 IS - 13 SP - 26703 EP - 26708 PB - Elsevier CY - Amsterdam, Netherlands AN - OPUS4-47097 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -