Title :
Precise localization of indoor mobile robots in FMS based on distributed vision
Author :
Wen, Fan ; Qu, Zhenshen ; Wang, Changhong ; Hu, Bin
Author_Institution :
Space Control & Inertia Technol. Res. Center, Harbin Inst. of Technol., Harbin
Abstract :
The knowledge of the pose and the orientation of mobile robot in its operating environment is of utmost importance for an autonomous robot. In this paper, we present a new robot localization method integrates distributed vision sensors with Monte Carlo localization (MCL) method. Firstly, an improved MCL method is used to estimates the posterior distribution of robot poses conditioned on sensor data. Secondly, the system uses distributed vision sensors to extract the feature of each running robotpsilas mark, and then use vision algorithm to determine each robotpsilas pose and orientation. Finally, Monte Carlo method is extended to integrate the detection information coming from vision sensors to localize robot. The result obtained in simulation and with real robots show that the method can measure the pose and orientation of each robot in the system accurately. Meanwhile, the reliability, real-time property and robustness of the system have been validated.
Keywords :
Monte Carlo methods; distributed sensors; estimation theory; feature extraction; mobile robots; pose estimation; robot vision; Monte Carlo localization; distributed vision sensors; feature extraction; indoor mobile robot; posterior distribution estimation; robot localization; robot poses; vision algorithm; Data mining; Feature extraction; Flexible manufacturing systems; Machine vision; Mobile robots; Monte Carlo methods; Robot localization; Robot sensing systems; Robot vision systems; Sensor systems; Distributed vision; Mixed fast particle filter; Mobile robots; Monte Carlo localization;
Conference_Titel :
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-2502-0
Electronic_ISBN :
978-1-4244-2503-7
DOI :
10.1109/ICAL.2008.4636572