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Abstract
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| A reliable estimation of the flight altitude in dynamic and unstructured indoor environments is an unsolved problem. Standalone available sensors, such as distance sensors, barometers and accelerometers, have multiple limitations in presence of non-flat ground surfaces, or in cluttered areas. To overcome these sensor limitations, maximizing their individual performance, this paper presents a modular EKF-based multi-sensor fusion approach for accurate vertical localization of multirotor UAVs in dynamic and unstructured indoor environments. The state estimator allows to combine the information provided by a variable number and type of sensors, including IMU, barometer and distance sensors, with the capabilities of sensor auto calibration and bias estimation, as well as a flexible configuration of the prediction and update stages. Several autonomous indoors real flights in unstructured environments have been conducted in order to validate our proposed state estimator, enabling the UAV to maintain the desired flight altitude when navigating over wide range of obstacles. Furthermore, it has been successfully used in IMAV 2016 competition. The presented work has been made publicly available to the scientific community as an open source software within the Aerostack1 framework. | |
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International
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Si |
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Congress
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Unmanned Aircraft Systems (ICUAS), 2017 International Conference on |
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960 |
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Place
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Miami, FL, USA, USA |
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Reviewers
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Si |
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ISBN/ISSN
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978-1-5090-4495-5 |
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10.1109/ICUAS.2017.7991467 |
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Start Date
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13/06/2017 |
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End Date
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16/06/2017 |
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From page
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1044 |
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To page
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1051 |
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