9783845417080 - a localisation and navigation system for an autonomous wheel loader: kalman filter sensor fusion applied in a real-time environment de lilja, robin (6 resultados)
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Taschenbuch. Condición: Neu. A Localisation and Navigation System for an Autonomous Wheel Loader | Kalman Filter Sensor Fusion Applied in a Real-time Environment | Robin Lilja | Taschenbuch | 104 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845417080 | Verantwortliche Person für die EU: BoD - Books on Demand,… In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Autonomous vehicles are an emerging trend in robotics, seen in a vast range of applications and environments. In an ongoing industrial project a fully autonomous wheel loader is being developed. This work (Master s Thesis) proposes…a solution to two of the main problems encountered when developing such vehicle - namely the problems of how to localise and navigate the vehicle in its task space. The proposed solution relies at its fulcrum - on the widely known and commonly accepted Kalman filter. Different vehicle models used by the Kalman filter for conducting sensor fusion are derived and evaluated on real datasets collected from different environments. In order to solve the problem of navigating the vehicle a waypoint-based path following algorithm is adopted. As a given objective by the industrial project the found solution is implemented and integrated into the real-time environment of a full size autonomous wheel loader, and where the final system is demonstrated as a proof of concept for utilising autonomous wheel loaders for repetitive work tasks. 104 pp. Englisch.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Lilja RobinRobin Lilja has been studying at Malardalen University (MDU, Sweden) and the University of Western Australia (UWA). In 2011 he graduated from MDU with the degree of Master of Science in Robot…ics Engineering. Currently he i.
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Autonomous vehicles are an emerging trend in robotics, seen in a vast range of applications and environments. In an ongoing industrial project a fully autonomous wheel loader is being developed. This work (Master's Thesis) proposes a so…lution to two of the main problems encountered when developing such vehicle - namely the problems of how to localise and navigate the vehicle in its task space. The proposed solution relies - at its fulcrum - on the widely known and commonly accepted Kalman filter. Different vehicle models used by the Kalman filter for conducting sensor fusion are derived and evaluated on real datasets collected from different environments. In order to solve the problem of navigating the vehicle a waypoint-based path following algorithm is adopted. As a given objective by the industrial project the found solution is implemented and integrated into the real-time environment of a full size autonomous wheel loader, and where the final system is demonstrated as a proof of concept for utilising autonomous wheel loaders for repetitive work tasks.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Autonomous vehicles are an emerging trend in robotics, seen in a vast range of applications and environments. In an ongoing industrial project a fully autonomous wheel loader is being developed. This work (Master s Thesis) proposes a sol…ution to two of the main problems encountered when developing such vehicle - namely the problems of how to localise and navigate the vehicle in its task space. The proposed solution relies at its fulcrum - on the widely known and commonly accepted Kalman filter. Different vehicle models used by the Kalman filter for conducting sensor fusion are derived and evaluated on real datasets collected from different environments. In order to solve the problem of navigating the vehicle a waypoint-based path following algorithm is adopted. As a given objective by the industrial project the found solution is implemented and integrated into the real-time environment of a full size autonomous wheel loader, and where the final system is demonstrated as a proof of concept for utilising autonomous wheel loaders for repetitive work tasks.
