Vision-Aided, Cooperative Navigation for Multiple Unmanned Vehicles

Bingham, Jason K

ISBN 10: 1288289146 ISBN 13: 9781288289141
Verlag: Biblioscholar, 2012
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The motivation of this research is to exploit three attributes of increased unmanned vehicle use for intelligence, surveillance, and reconnaissance missions. These attributes are: increased numbers of unmanned vehicles, on-board vision, and wireless communications. The research begins with the development of a cooperative navigation system based on the measurement of vehicle position relative to shared landmark position estimates. Each vehicle in the network locates landmarks using it's on-board vision system and transmits the data to all other system vehicles. After receiving data from the other vehicles, the system fuses the landmarks with on-board measurements using a federated filter architecture. Simulations of the cooperative system, with and without ranging, are compared to a non-cooperative simulation. The comparison is performed using four platform motion scenarios: stationary, linear, angular, and full motion. The simulation results demonstrate position error estimate improvements of 0.5cm to 1cm. Additionally; the stationary and linear motion scenarios demonstrate attitude observability difficulties eliminated by the introduction of angular motion.

Reseña del editor: The motivation of this research is to exploit three attributes of increased unmanned vehicle use for intelligence, surveillance, and reconnaissance missions. These attributes are: increased numbers of unmanned vehicles, on-board vision, and wireless communications. The research begins with the development of a cooperative navigation system based on the measurement of vehicle position relative to shared landmark position estimates. Each vehicle in the network locates landmarks using it's on-board vision system and transmits the data to all other system vehicles. After receiving data from the other vehicles, the system fuses the landmarks with on-board measurements using a federated filter architecture. Simulations of the cooperative system, with and without ranging, are compared to a non-cooperative simulation. The comparison is performed using four platform motion scenarios: stationary, linear, angular, and full motion. The simulation results demonstrate position error estimate improvements of 0.5cm to 1cm. Additionally; the stationary and linear motion scenarios demonstrate attitude observability difficulties eliminated by the introduction of angular motion.

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Titel: Vision-Aided, Cooperative Navigation for ...
Verlag: Biblioscholar
Erscheinungsdatum: 2012
Einband: Softcover
Zustand: New

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Bingham, Jason K.
Verlag: BIBLIOSCHOLAR, 2012
ISBN 10: 1288289146 ISBN 13: 9781288289141
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Anbieter: moluna, Greven, Deutschland

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Zustand: New. KlappentextrnrnThe motivation of this research is to exploit three attributes of increased unmanned vehicle use for intelligence, surveillance, and reconnaissance missions. These attributes are: increased numbers of unmanned vehicles, on-board v. Artikel-Nr. 6553361

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Jason K Bingham
Verlag: Biblioscholar Nov 2012, 2012
ISBN 10: 1288289146 ISBN 13: 9781288289141
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Taschenbuch. Zustand: Neu. Neuware - The motivation of this research is to exploit three attributes of increased unmanned vehicle use for intelligence, surveillance, and reconnaissance missions. These attributes are: increased numbers of unmanned vehicles, on-board vision, and wireless communications. The research begins with the development of a cooperative navigation system based on the measurement of vehicle position relative to shared landmark position estimates. Each vehicle in the network locates landmarks using it's on-board vision system and transmits the data to all other system vehicles. After receiving data from the other vehicles, the system fuses the landmarks with on-board measurements using a federated filter architecture. Simulations of the cooperative system, with and without ranging, are compared to a non-cooperative simulation. The comparison is performed using four platform motion scenarios: stationary, linear, angular, and full motion. The simulation results demonstrate position error estimate improvements of 0.5cm to 1cm. Additionally; the stationary and linear motion scenarios demonstrate attitude observability difficulties eliminated by the introduction of angular motion. Artikel-Nr. 9781288289141

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