Uncertainty and imprecision modeling for the mobile robot localization problem

Autor:	Arnaud Clerentin, Bruno Marhic, Anne-Marie Jolly-Desodt, Laurent Delahoche, M. Delafosse
Rok vydání:	2007
Předmět:	Computer science business.industry Mobile robot Transferable belief model Sensor fusion Odometer Robot localization Artificial Intelligence Local consistency Robot Computer vision Artificial intelligence business 3d localization
Zdroj:	Autonomous Robots. 24:267-283
ISSN:	1573-7527 0929-5593
DOI:	10.1007/s10514-007-9066-3
Popis:	This article deals with uncertainty and imprecision treatment during the mobile robot localization process. The imprecision determination is based on the use of the interval formalism. Indeed, the mobile robot is equipped with an exteroceptive sensor and odometers. The imprecise data given by these two sensors are fused by constraint propagation on intervals. At the end of the algorithm, we get 3D localization subpaving which is supposed to contain the robot's position in a guaranteed way. Concerning the uncertainty, it is managed through a propagation architecture based on the use of the Transferable Belief Model of Smets. This architecture enables to propagate uncertainty from low level data (sensor data) in order to quantify the global uncertainty of the robot localization estimation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b87a8c04e87f73bc4cd466ef15c40f23 https://doi.org/10.1007/s10514-007-9066-3 Zobrazit plný text záznamu Full text from SpringerLink