DocumentCode
2703678
Title
Incremental construction of the saturated-GVG for multi-hypothesis topological SLAM
Author
Tao, Tong ; Tully, Stephen ; Kantor, George ; Choset, Howie
Author_Institution
Coll. of Inf. Tech. Sci., Nankai Univ., Tianjin, China
fYear
2011
fDate
9-13 May 2011
Firstpage
3072
Lastpage
3077
Abstract
The generalized Voronoi graph (GVG) is a topological representation of an environment that can be incrementally constructed with a mobile robot using sensor-based control. However, because of sensor range limitations, the GVG control law will fail when the robot moves into a large open area. This paper discusses an extended GVG approach to topological navigation and mapping: the saturated generalized Voronoi graph (S-GVG), for which the robot employs an additional wall-following behavior to navigate along obstacles at the range limit of the sensor. In this paper, we build upon previous work related to the S-GVG and provide two important contributions: 1) a rigorous discussion of the control laws and algorithm modifications that are necessary for incremental construction of the S-GVG with a mobile robot, and 2) a method for incorporating the S-GVG into a novel multi-hypothesis SLAM algorithm for loop-closing and localization. Experiments with a wheeled mobile robot in an office-like environment validate the effectiveness of the proposed approach.
Keywords
SLAM (robots); computational geometry; mobile robots; path planning; sensors; topology; Voronoi graph; incremental construction; multihypothesis SLAM algorithm; multihypothesis topological SLAM; saturated-GVG control; sensor range limitation; sensor-based control; topological representation; wheeled mobile robot; Delay; Image edge detection; Mobile robots; Navigation; Simultaneous localization and mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation (ICRA), 2011 IEEE International Conference on
Conference_Location
Shanghai
ISSN
1050-4729
Print_ISBN
978-1-61284-386-5
Type
conf
DOI
10.1109/ICRA.2011.5980524
Filename
5980524
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