13 research outputs found

    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

    Formation-Based Odour Source Localisation Using Distributed Terrestrial and Marine Robotic Systems

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    This thesis tackles the problem of robotic odour source localisation, that is, the use of robots to find the source of a chemical release. As the odour travels away from the source, in the form of a plume carried by the wind or current, small scale turbulence causes it to separate into intermittent patches, suppressing any gradients and making this a particularly challenging search problem. We focus on distributed strategies for odour plume tracing in the air and in the water and look primarily at 2D scenarios, although novel results are also presented for 3D tracing. The common thread to our work is the use of multiple robots in formation, each outfitted with odour and flow sensing devices. By having more than one robot, we can gather observations at different locations, thus helping overcome the difficulties posed by the patchiness of the odour concentration. The flow (wind or current) direction is used to orient the formation and move the robots up-flow, while the measured concentrations are used to centre the robots in the plume and scale the formation to trace its limits. We propose two formation keeping methods. For terrestrial and surface robots equipped with relative or absolute positioning capabilities, we employ a graph-based formation controller using the well-known principle of Laplacian feedback. For underwater vehicles lacking such capabilities, we introduce an original controller for a leader-follower triangular formation using acoustic modems with ranging capabilities. The methods we propose underwent extensive experimental evaluation in high-fidelity simulations and real-world trials. The marine formation controller was implemented in MEDUSA autonomous vehicles and found to maintain a stable formation despite the multi-second ranging period. The airborne plume tracing algorithm was tested using compact Khepera robots in a wind tunnel, yielding low distance overheads and reduced tracing error. A combined approach for marine plume tracing was evaluated in simulation with promising results

    Formation-Based Odour Source Localisation Using Distributed Terrestrial and Marine Robotic Systems

    Get PDF
    This thesis tackles the problem of robotic odour source localisation, that is, the use of robots to find the source of a chemical release. As the odour travels away from the source, in the form of a plume carried by the wind or current, small scale turbulence causes it to separate into intermittent patches, suppressing any gradients and making this a particularly challenging search problem. We focus on distributed strategies for odour plume tracing in the air and in the water and look primarily at 2D scenarios, although novel results are also presented for 3D tracing. The common thread to our work is the use of multiple robots in formation, each outfitted with odour and flow sensing devices. By having more than one robot, we can gather observations at different locations, thus helping overcome the difficulties posed by the patchiness of the odour concentration. The flow (wind or current) direction is used to orient the formation and move the robots up-flow, while the measured concentrations are used to centre the robots in the plume and scale the formation to trace its limits. We propose two formation keeping methods. For terrestrial and surface robots equipped with relative or absolute positioning capabilities, we employ a graph-based formation controller using the well-known principle of Laplacian feedback. For underwater vehicles lacking such capabilities, we introduce an original controller for a leader-follower triangular formation using acoustic modems with ranging capabilities. The methods we propose underwent extensive experimental evaluation in high-fidelity simulations and real-world trials. The marine formation controller was implemented in MEDUSA autonomous vehicles and found to maintain a stable formation despite the multi-second ranging period. The airborne plume tracing algorithm was tested using compact Khepera robots in a wind tunnel, yielding low distance overheads and reduced tracing error. A combined approach for marine plume tracing was evaluated in simulation with promising results

    Underwater Vehicles

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    For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

    Reinforcement learning of visually guided spatial goal directed movement

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    A range of visually guided, spatial goal directed tasks are investigated, using a computational neuroethology approach. Animats are embedded within a bounded, 2-D environment, and map a 1-D visual array, through a convolution network, to a topography preserving motor array that stochastically determines the direction of movement. Temporal difference reinforcement learning modifies the convolution network in response to a reinforcement signal received only at the goal location. Three forms of visual coding are compared: multiscale coding, where the visual array is convolved by Laplacian of Gaussian filters at a range of spatial scales before convolution to determine the motor array; rectified multiscale coding, where the multiscale array is split into positive and negative components; and intensity coding, where the unfiltered visual array is convolved to determine the motor array. After learning, animats are examined in terms of performance, behaviour and internal structure. When animats learn to approach a solitary circle, of randomly varying contrast, rectified multiscale coding animats learn to outperform multiscale and intensity coding animats in both independent and coarse scale noise conditions. Analysis of the learned internal structure shows that rectified multiscale filtering facilitates learning by enabling detection of the circle at scales least affected by noise. Cartwright and Collett (1983) showed that honeybees learn the angle subtended by a featureless landmark to guide movement to a food source at a fixed distance from the landmark, and furthermore, when tested with only the edges of the landmark, still search in the same location. In a simulation of this experiment, animats are reinforced for moving to where the angle subtended by a solitary circle falls within a certain range. Rectified multiscale filtering leads to better performing animats, with fewer hidden units, in both independent and coarse scale visual noise conditions, though for different reasons in each case. Only those animats with rectified multiscale filtering, that learn in the presence of coarse scale noise, show similar generalisation to the honeybees. Collett, Cartwright and Smith (1986) trained gerbils to search at locations relative to arrangemments of landmarks and tested their search patterns in modifications of the training arrangements. These experiments are simulated with landmark distance coded as either a 1-D intensity array, or a 2-D vector array, plus a simple compass sense. Vector coding animats significantly outperform those using intensity coding and do so with fewer hidden units. Furthermore, vector coding animats show a close match to gerbil behaviour in tests with modified landmark arrangements

    Active touch sensing in pinnipeds

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    Active touch sensing in humans is characterised by making purposive movements with their fingertips. These movements are task-specific to maximise the relevant information gathered from an object. In whisker-touch sensing, previous research has suggested that whisker movements are purposive, but no one has ever examined task-specific whisker movements in any animal. Pinnipeds are whisker specialists, with long, mobile, sensitive whiskers and diverse whisker morphologies. The aim of this PhD is to investigate active touch sensing in Pinnipeds (seals, sea lions and walrus), by: i) describing whisker morphology; ii) comparing and quantifying whisker movements; and iii) characterising task-dependency of whisker movements during texture, size and luminance discrimination tasks. Pinnipeds with long, numerous whiskers, such as California sea lions (Zalophus californianus) and Stellar sea lions (Eumetopias jubatus) have larger infraorbital foramen (IOF) sizes and therefore, more sensitive whiskers. The IOF being a small hole in the skull, allowing the infraorbital nerve (ION) to pass through, which supplies sensation to the whiskers. Comparing whisker movements in Harbor seals (Phoca vitulina), California sea lions and Pacific walrus (Odobenidae rosmarus), showed these species all protracted their whiskers forwards and oriented their head towards a moving fish stimulus. However, California sea lions moved their whiskers more than the other species, and independently of the head. Due to the movement capabilities and sensitivity of whiskers in California sea lions, this species was used to investigate whether whiskers can be moved in a task-specific way. Results suggested that California sea lions make task-specific movements, by feeling around the edge of different-sized shapes, and focussing and spreading their whiskers on the centre of different-textured shapes. Therefore, California sea lion whiskers are controlled like a true active touch sensory system, similar to human fingertips. I suggest that active touch sensing is likely to efficiently guide foraging and prey capture in dark, murky waters in these animals. Moreover, the complexity of California sea lion whisker movements and their subsequent behaviours makes them a good candidate from which to further investigate animal decision-making, perception and cognition

    Sensor Signal and Information Processing II

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    In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

    Modelling, Simulation and Data Analysis in Acoustical Problems

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    Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years
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