16 research outputs found

    Airborne chemical sensing with mobile robots

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    Airborne chemical sensing with mobile robots has been an active research areasince the beginning of the 1990s. This article presents a review of research work in this field,including gas distribution mapping, trail guidance, and the different subtasks of gas sourcelocalisation. Due to the difficulty of modelling gas distribution in a real world environmentwith currently available simulation techniques, we focus largely on experimental work and donot consider publications that are purely based on simulations

    Towards Odor-Sensitive Mobile Robots

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    J. Monroy, J. Gonzalez-Jimenez, "Towards Odor-Sensitive Mobile Robots", Electronic Nose Technologies and Advances in Machine Olfaction, IGI Global, pp. 244--263, 2018, doi:10.4018/978-1-5225-3862-2.ch012 Versión preprint, con permiso del editorOut of all the components of a mobile robot, its sensorial system is undoubtedly among the most critical ones when operating in real environments. Until now, these sensorial systems mostly relied on range sensors (laser scanner, sonar, active triangulation) and cameras. While electronic noses have barely been employed, they can provide a complementary sensory information, vital for some applications, as with humans. This chapter analyzes the motivation of providing a robot with gas-sensing capabilities and also reviews some of the hurdles that are preventing smell from achieving the importance of other sensing modalities in robotics. The achievements made so far are reviewed to illustrate the current status on the three main fields within robotics olfaction: the classification of volatile substances, the spatial estimation of the gas dispersion from sparse measurements, and the localization of the gas source within a known environment

    Smelling Nano Aerial Vehicle for Gas Source Localization and Mapping

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    This paper describes the development and validation of the currently smallest aerial platform with olfaction capabilities. The developed Smelling Nano Aerial Vehicle (SNAV) is based on a lightweight commercial nano-quadcopter (27 g) equipped with a custom gas sensing board that can host up to two in situ metal oxide semiconductor (MOX) gas sensors. Due to its small form-factor, the SNAV is not a hazard for humans, enabling its use in public areas or inside buildings. It can autonomously carry out gas sensing missions of hazardous environments inaccessible to terrestrial robots and bigger drones, for example searching for victims and hazardous gas leaks inside pockets that form within the wreckage of collapsed buildings in the aftermath of an earthquake or explosion. The first contribution of this work is assessing the impact of the nano-propellers on the MOX sensor signals at different distances to a gas source. A second contribution is adapting the 'bout' detection algorithm, proposed by Schmuker et al. (2016) to extract specific features from the derivative of the MOX sensor response, for real-time operation. The third and main contribution is the experimental validation of the SNAV for gas source localization (GSL) and mapping in a large indoor environment (160 m²) with a gas source placed in challenging positions for the drone, for example hidden in the ceiling of the room or inside a power outlet box. Two GSL strategies are compared, one based on the instantaneous gas sensor response and the other one based on the bout frequency. From the measurements collected (in motion) along a predefined sweeping path we built (in less than 3 min) a 3D map of the gas distribution and identified the most likely source location. Using the bout frequency yielded on average a higher localization accuracy than using the instantaneous gas sensor response (1.38 m versus 2.05 m error), however accurate tuning of an additional parameter (the noise threshold) is required in the former case. The main conclusion of this paper is that a nano-drone has the potential to perform gas sensing tasks in complex environments

    Drones and Sensors Ecosystem to Maximise the “Storm Effects” in Case of CBRNe Dispersion in Large Geographic Areas

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    The advancements in the field of robotics, specifically in the aerial robotics, combined with technological improvements of the capability of drones, have increased dramatically the use of these devices as a valuable tool in a wide range of applications. From civil to commercial and military area, the requirements in the emerging application for monitoring complex scenarios that are potentially dangerous for operators give rise to the need of a more powerful and sophisticated approach. This work aims at proposing the use of swarm drones to increase plume detection, tracking and source declaration for chemical releases. The several advantages which this technology may lead to this research and application fields are investigated, as well as the research and technological activities to be performed to make swarm drones efficient, reliable, and accurate

    Drones and sensors ecosystem to maximise the "storm effects" in case of cbrne dispersion in large geographic areas

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    Advances in Gas Sensing and Mapping for Mobile Robotics

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    Esta tesis aborda el problema de la detección, cuantificación y mapeo de sustancias olorosas empleando un robot móvil equipado con una nariz electrónica. En robótica móvil se emplean los sistemas de muestreo abierto (Open Sampling Systems - OSS), los cuales están caracterizados por introducir importantes fuentes de incertidumbre en las medidas de gases obtenidas. Estas fuentes de incertidumbre se deben principalmente a los mecanismos de dispersión de los gases y al comportamiento dinámico de los sensores de gas, los cuales complican en gran medida las tareas de detección de gases con robots móviles. En esta tesis se proponen contribuciones en tres sub-áreas de la robótica móvil olfativa. Referente a la detección de sustancias olorosas en OSS, y especialmente enfocando a paliar el problema de la lenta recuperación de los sensores basados en tecnología de óxido de metal (Metal Oxide Semiconductor - MOX), se proponen dos contribuciones: un nuevo diseño de nariz electrónica (Multi Chamber Electronic Nose - MCE-nose) y un enfoque basado en el modelado dinámico de estos sensores. Referente a la cuantificación de gases, se propone un novedoso enfoque probabilístico el cual permite la estimación de la concentración del gas junto con su incertidumbre asociada, algo imprescindible para aplicaciones de robótica olfativa. Finalmente, relacionado con el estudio de la distribución espacial de los gases, esta tesis contribuye con la propuesta de un método probabilístico para la generación de mapas de gas. Este novedoso método permite, por primera vez, considerar tanto los obstáculos presentes en el entorno, como el envejecimiento (factor temporal) de las medidas de gas

    Environmental chemical sensing using small drones: A review

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    Recent advances in miniaturization of chemical instrumentation and in low-cost small drones are catalyzing exponential growth in the use of such platforms for environmental chemical sensing applications. The versatility of chemically sensitive drones is reflected by their rapid adoption in scientific, industrial, and regulatory domains, such as in atmospheric research studies, industrial emission monitoring, and in enforcement of environmental regulations. As a result of this interdisciplinarity, progress to date has been reported across a broad spread of scientific and non-scientific databases, including scientific journals, press releases, company websites, and field reports. The aim of this paper is to assemble all of these pieces of information into a comprehensive, structured and updated review of the field of chemical sensing using small drones. We exhaustively review current and emerging applications of this technology, as well as sensing platforms and algorithms developed by research groups and companies for tasks such as gas concentration mapping, source localization, and flux estimation. We conclude with a discussion of the most pressing technological and regulatory limitations in current practice, and how these could be addressed by future research

    On the use of autonomous unmanned vehicles in response to hazardous atmospheric release incidents

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    Recent events have induced a surge of interest in the methods of response to releases of hazardous materials or gases into the atmosphere. In the last decade there has been particular interest in mapping and quantifying emissions for regulatory purposes, emergency response, and environmental monitoring. Examples include: responding to events such as gas leaks, nuclear accidents or chemical, biological or radiological (CBR) accidents or attacks, and even exploring sources of methane emissions on the planet Mars. This thesis presents a review of the potential responses to hazardous releases, which includes source localisation, boundary tracking, mapping and source term estimation. [Continues.]</div

    Information-Driven Gas Distribution Mapping for Autonomous Mobile Robots.

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    The ability to sense airborne pollutants with mobile robots provides a valuable asset for domains such as industrial safety and environmental monitoring. Oftentimes, this involves detecting how certain gases are spread out in the environment, commonly referred to as a gas distribution map, to subsequently take actions that depend on the collected information. Since the majority of gas transducers require physical contact with the analyte to sense it, the generation of such a map usually involves slow and laborious data collection from all key locations. In this regard, this paper proposes an efficient exploration algorithm for 2D gas distribution mapping with an autonomous mobile robot. Our proposal combines a Gaussian Markov random field estimator based on gas and wind flow measurements, devised for very sparse sample sizes and indoor environments, with a partially observable Markov decision process to close the robot’s control loop. The advantage of this approach is that the gas map is not only continuously updated, but can also be leveraged to choose the next location based on how much information it provides. The exploration consequently adapts to how the gas is distributed during run time, leading to an efficient sampling path and, in turn, a complete gas map with a relatively low number of measurements. Furthermore, it also accounts for wind currents in the environment, which improves the reliability of the final gas map even in the presence of obstacles or when the gas distribution diverges from an ideal gas plume. Finally, we report various simulation experiments to evaluate our proposal against a computer-generated fluid dynamics ground truth, as well as physical experiments in a wind tunnel.Partial funding for open access charge: Universidad de Málag
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