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Título : Using the Average Landmark Vector Method for Robot Homing.
Autor : Goldhoorn, Alex ; Ramisa, Arnau; Lopez de Mantaras, Ramon; Toledo, Ricardo
Palabras clave : Artificial Intelligence
Mobile Robot Homing
Average Landmark Vector
Invariant Features
Fecha de publicación : 2007
Editor: IOS Press
Citación : Artificial Intelligence Research and Development. CCIA'07: 10th International Conference of the ACIA. Andorra, October 25-26. Frontiers in Artificial Intelligence and Applications, Vol. 163. IOS Press. p.p.: 331-338. 2007.
Resumen: Several methods can be used for a robot to return to a previously visited position. In our approach we use the average landmark vector method to calculate a homing vector which should point the robot to the destination. This approach was tested in a simulated environment, where panoramic projections of features were used. To evaluate the robustness of the method, several parameters of the simulation were changed such as the length of the walls and the number of features, and also several disturbance factors were added to the simulation such as noise and occlusion. The simulated robot performed really well. Randomly removing 50% of the features resulted in a mean of 85% successful runs. Even adding more than 100% fake features did not have any significant result on the performance.
Descripción : The original publication ia available at http://www.booksonline.iospress.nl/Content/View.aspx?piid=7638
URI : http://hdl.handle.net/10261/3627
ISBN : 978-1-58603-798-7
ISSN: 0922-6389
Aparece en las colecciones: (IIIA) Comunicaciones congresos
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