Isbn: 9783838382265 - multi-agent visual-slam algorithms on autonomous robots: multi-robot mapping (10 risultati)

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2010

    3838382269 / 9783838382265

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2010

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing 2010-06-29, 2010

    3838382269 / 9783838382265

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2010

    3838382269 / 9783838382265

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    Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2013

    3838382269 / 9783838382265

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    Taschenbuch. Condizione: Neu. Multi-Agent Visual-SLAM Algorithms on Autonomous Robots | Multi-Robot Mapping | Nezih Ergin Özkucur | Taschenbuch | 120 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783838382265 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2010

    3838382269 / 9783838382265

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2010

    3838382269 / 9783838382265

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    PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Jun 2010, 2010

    3838382269 / 9783838382265

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Simultaneous Localization and Mapping (SLAM) problem is one of the most challenging problems in robot navigation. The problem addresses autonomously exploring and mapping an unknown environment without prior knowledge (of features). The robot should generate the map of the environment and estimate its pose with respect to the map. An extension of this problem to the distributed multi-robot platform is a popular research topic for its challenges and commitments. Multiple cooperative robots exploring an area would decrease exploration time and increase the accuracy. This work introduces the application of two successful SLAM solution techniques to the multi-robot domain using visual sensors and non-unique landmarks. There are two contributions to the literature: Evolutionary Strategies (ES) is used to calibrate the parameters of the Extended Kalman Filter-SLAM (EKF-SLAM) method with supervised data, and a novel map merging method with uncertainty propagation is introduced for the Fast-SLAM algorithm. The developed algorithms are tested in both simulated and real robot experiments and the improvements and applicability of the developed methods are shown with the results. 120 pp. Englisch.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2010

    3838382269 / 9783838382265

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Simultaneous Localization and Mapping (SLAM) problem is one of the most challenging problems in robot navigation. The problem addresses autonomously exploring and mapping an unknown environment without prior knowledge (of features). The robot should generate the map of the environment and estimate its pose with respect to the map. An extension of this problem to the distributed multi-robot platform is a popular research topic for its challenges and commitments. Multiple cooperative robots exploring an area would decrease exploration time and increase the accuracy. This work introduces the application of two successful SLAM solution techniques to the multi-robot domain using visual sensors and non-unique landmarks. There are two contributions to the literature: Evolutionary Strategies (ES) is used to calibrate the parameters of the Extended Kalman Filter-SLAM (EKF-SLAM) method with supervised data, and a novel map merging method with uncertainty propagation is introduced for the Fast-SLAM algorithm. The developed algorithms are tested in both simulated and real robot experiments and the improvements and applicability of the developed methods are shown with the results.

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Jun 2010, 2010

    3838382269 / 9783838382265

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The Simultaneous Localization and Mapping (SLAM) problem is one of the most challenging problems in robot navigation. The problem addresses autonomously exploring and mapping an unknown environment without prior knowledge (of features). The robot should generate the map of the environment and estimate its pose with respect to the map. An extension of this problem to the distributed multi-robot platform is a popular research topic for its challenges and commitments. Multiple cooperative robots exploring an area would decrease exploration time and increase the accuracy. This work introduces the application of two successful SLAM solution techniques to the multi-robot domain using visual sensors and non-unique landmarks. There are two contributions to the literature: Evolutionary Strategies (ES) is used to calibrate the parameters of the Extended Kalman Filter-SLAM (EKF-SLAM) method with supervised data, and a novel map merging method with uncertainty propagation is introduced for the Fast-SLAM algorithm. The developed algorithms are tested in both simulated and real robot experiments and the improvements and applicability of the developed methods are shown with the results.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch.