Title :
Hybrid Mobile Robot Indoor Localization Using Large-Scale Metric-Topological Map
Author_Institution :
Res. Center of Inf. & Control, Dalian Univ. of Technol.
Abstract :
Localization is an essential task for an autonomous mobile robot´s indoor navigation. Based on the metric-topological environment modeling, a hybrid localization method, pose tracking in local metric map and global localization in topological map, are used in this paper to carry out accurate and robust localization in semi-structured indoor environment. In order to guarantee the effectiveness of global localization and also solve the kidnapped robot problem in dynamic environment with some unexpected collisions, a novel normalized topological node weights filter (NTNWF) algorithm is presented, which makes mobile robot´s localization in large-scale topological map with closing loops and symmetric configurations available and efficient in least motion steps. Experiment results implemented in both SmartROB-2 mobile robot and the simulation software designed specially for NTNWF algorithm show the hybrid localization method´s validity and practicability
Keywords :
control engineering computing; mobile robots; motion control; navigation; path planning; topology; SmartROB-2; autonomous mobile robot indoor navigation; hybrid localization method; large-scale metric-topological map; mobile robot indoor localization; normalized topological node weights filter algorithm; pose tracking; Algorithm design and analysis; Filters; Indoor environments; Large-scale systems; Mobile robots; Navigation; Robot localization; Robustness; Software algorithms; Software design; Hybrid localization; extended Kalman filter; metric-topological map; normalized topological node weights filter;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713752
