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Item type:Publication, Access status: without files , An integrated approach to navigation and control in micro underwater robotics using radio-frequency localizationNavigation and control are a largely unsolved problems for micro autonomous underwater vehicles (). The main challenges are due to the lack of accurate underwater localization systems, which fit on-board of . In this work, we present an integrated navigation and control architecture consisting of a low-cost embedded localization module and an underwater way-point tracking controller, which fulfills the requirements of . The performance of the navigation and control system is benchmarked in two different experimental scenarios.Publicationtype: Conference Paper211 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Embedded spherical localization for micro underwater vehicles based on attenuation of electro-magnetic carrier signals(Multidisciplinary Digital Publishing Institute (MDPI), 2017-04-26); ; ; ; Self-localization is one of the most challenging problems for deploying micro autonomous underwater vehicles (μAUV) in confined underwater environments. This paper extends a recently-developed self-localization method that is based on the attenuation of electro-magnetic waves, to the μAUV domain. We demonstrate a compact, low-cost architecture that is able to perform all signal processing steps present in the original method. The system is passive with one-way signal transmission and scales to possibly large μAUV fleets. It is based on the spherical localization concept. We present results from static and dynamic position estimation experiments and discuss the tradeoffs of the system.Publicationtype: Journal ArticleScopus© Citations 17 710 671 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Learning a deep neural net policy for end-to-end control of autonomous vehiclesDeep neural networks are frequently used for computer vision, speech recognition and text processing. The reason is their ability to regress highly nonlinear functions. We present an end-to-end controller for steering autonomous vehicles based on a convolutional neural network (CNN). The deployed framework does not require explicit hand-engineered algorithms for lane detection, object detection or path planning. The trained neural net directly maps pixel data from a front-facing camera to steering commands and does not require any other sensors. We compare the controller performance with the steering behavior of a human driver.Publicationtype: Conference Paper139 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Towards a hyperbolic acoustic one-way localization system for underwater swarm robotics(2016-06-08); ; ; ; A hyperbolic acoustic system for underwater robot self-localization is presented. Anchored transducers send acoustic signals which are observed by a receiver. The system is passive with one-way signal transmission. Time differences of arrival (TDOAs) between the emitted signals are estimated by the receiver via cross-correlation. These TDOAs are fed to an Extended Kalman Filter to estimate the global position of the receiver. We describe the complete signal processing chain as well as challenges in hardware and software design. Experimental results in air and water show the feasibility of the system. This paper demonstrates that acoustic one-way localization is possible with off-the-shelf hardware in experimental test tanks.Publicationtype: Conference Paper109