Autonomous unmanned vehicles require the ability to maneuver within their environments safely and efficiently. The problem of generating these traversable, collision-free paths is known as motion planning. While much work has been done in this field, the majority of the existing motion planning algorithms either fail to consider the kinodynamic constraints of the vehicle or is too computationally intensive to be performed online. The presented motion planning algorithm mitigates these issues by using kinodynamically feasible motion primitives to enforce vehicle constraints, while exploiting the computational efficiency and scalability of probabilistic roadmap planners. The result is an online motion planner that is capable of generating safe, traversable paths to any specified destination in an unknown 3D environment. This approach has been experimentally verified using quadrotor helicopters and skid-steer ground rovers.
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Peiyi Chen has developed planning algorithms and control strategies for a a variety of autonomous unmanned vehicles, including quadrotor helicopters and skid-steer ground rovers. He is a member of the Waterloo Autonomous Vehicles Lab at the University of Waterloo, where he received his MASc. degree in mechanical and mechatronics engineering.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Autonomous unmanned vehicles require the ability to maneuver within their environments safely and efficiently. The problem of generating these traversable, collision-free paths is known as motion planning. While much work has been done in this field, the majority of the existing motion planning algorithms either fail to consider the kinodynamic constraints of the vehicle or is too computationally intensive to be performed online. The presented motion planning algorithm mitigates these issues by using kinodynamically feasible motion primitives to enforce vehicle constraints, while exploiting the computational efficiency and scalability of probabilistic roadmap planners. The result is an online motion planner that is capable of generating safe, traversable paths to any specified destination in an unknown 3D environment. This approach has been experimentally verified using quadrotor helicopters and skid-steer ground rovers. 112 pp. Englisch. Codice articolo 9783846545522
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Autonomous unmanned vehicles require the ability to maneuver within their environments safely and efficiently. The problem of generating these traversable, collision-free paths is known as motion planning. While much work has been done in this field, the majority of the existing motion planning algorithms either fail to consider the kinodynamic constraints of the vehicle or is too computationally intensive to be performed online. The presented motion planning algorithm mitigates these issues by using kinodynamically feasible motion primitives to enforce vehicle constraints, while exploiting the computational efficiency and scalability of probabilistic roadmap planners. The result is an online motion planner that is capable of generating safe, traversable paths to any specified destination in an unknown 3D environment. This approach has been experimentally verified using quadrotor helicopters and skid-steer ground rovers. Codice articolo 9783846545522
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Da: Books Puddle, Woodside, NY, U.S.A.
Condizione: New. Codice articolo 26358900589
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Da: Majestic Books, Hounslow, Regno Unito
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Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chen PeiyiPeiyi Chen has developed planning algorithms and control strategies for a a variety of autonomous unmanned vehicles, including quadrotor helicopters and skid-steer ground rovers. He is a member of the Waterloo Autonomous Ve. Codice articolo 5498096
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Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND. Codice articolo 18358900583
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Autonomous unmanned vehicles require the ability to maneuver within their environments safely and efficiently. The problem of generating these traversable, collision-free paths is known as motion planning. While much work has been done in this field, the majority of the existing motion planning algorithms either fail to consider the kinodynamic constraints of the vehicle or is too computationally intensive to be performed online. The presented motion planning algorithm mitigates these issues by using kinodynamically feasible motion primitives to enforce vehicle constraints, while exploiting the computational efficiency and scalability of probabilistic roadmap planners. The result is an online motion planner that is capable of generating safe, traversable paths to any specified destination in an unknown 3D environment. This approach has been experimentally verified using quadrotor helicopters and skid-steer ground rovers.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch. Codice articolo 9783846545522
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Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 112 pages. 8.66x5.91x0.26 inches. In Stock. Codice articolo 384654552X
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paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA829384654552X6
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