Baillio Brad (10 results)

Condition: New.

Paperback. Condition: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.

Paperback. Condition: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.

Taschenbuch. Condition: Neu. Multirobot Tethering | Solving the Localization Problem | Brad Baillio | Taschenbuch | 64 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659461361 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. Tracking and controlling a secondary robot introduces a known feature in the environment which can ensure a high confidence estimate. From this knowledge, an autonomous robot can confidently navigate in even the most difficult (featureless) environments. 64 pp. Englisch.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Baillio BradHe grew up in San Antonio, Texas. He currently resides in Utah with his talented wife and three terrific children. He works as a Robotics Engineer with a focus on Perception Products that can make an impact in Vehicle .

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. Tracking and controlling a secondary robot introduces a known feature in the environment which can ensure a high confidence estimate. From this knowledge, an autonomous robot can confidently navigate in even the most difficult (featureless) environments.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. Tracking and controlling a secondary robot introduces a known feature in the environment which can ensure a high confidence estimate. From this knowledge, an autonomous robot can confidently navigate in even the most difficult (featureless) environments.