Title :
LSRII feature based particle filter localization for mobile robot
Author :
Zhao, Fengda ; Kong, Lingfu ; Li, Xianshan
Author_Institution :
Coll. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao
Abstract :
To improve the localization capability of the mobile robot in a crowded and unorderly indoor environment, an approach for extracting LSRII (Local Salient Region Integral Invariant) features is proposed. The approach extracts integral invariant features in salient regions in an image. The global localization is achieved by applying LSRII features in particle filter localization. The practical experiments illustrate that our approach is reliable in a crowded and unorderly indoor environment.
Keywords :
feature extraction; mobile robots; particle filtering (numerical methods); LSRII feature; integral invariant features; local salient region integral invariant; mobile robot; particle filter localization; salient regions; unorderly indoor environment; Data mining; Density measurement; Extraterrestrial measurements; Feature extraction; Indoor environments; Intelligent control; Mobile robots; Particle filters; Position measurement; Robot sensing systems; LSRII feature; kernel function; particle filter localization;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4593290
