Title :
A two-view based multilayer feature graph for robot navigation
Author :
Haifeng Li ; Dezhen Song ; Yan Lu ; Jingtai Liu
Author_Institution :
Inst. of Robot. & Autom. Inf. Syst., Nankai Univ., Tianjin, China
Abstract :
To facilitate scene understanding and robot navigation in a modern urban area, we design a multilayer feature graph (MFG) based on two views from an on-board camera. The nodes of an MFG are features such as scale invariant feature transformation (SIFT) feature points, line segments, lines, and planes while edges of the MFG represent different geometric relationships such as adjacency, parallelism, collinearity, and coplanarity. MFG also connects the features in two views and the corresponding 3D coordinate system. Building on SIFT feature points and line segments, MFG is constructed using feature fusion which incrementally, iteratively, and extensively verifies the aforementioned geometric relationships using random sample consensus (RANSAC) framework. Physical experiments show that MFG can be successfully constructed in urban area and the construction method is demonstrated to be very robust in identifying feature correspondence.
Keywords :
graph theory; image sensors; mobile robots; path planning; 3D coordinate system; adjacency; collinearity; coplanarity; feature fusion; on-board camera; parallelism; random sample consensus framework; robot navigation; scale invariant feature transformation feature points; two-view based multilayer feature graph; Buildings; Cameras; Feature extraction; Navigation; Robot kinematics; Sensors;
Conference_Titel :
Robotics and Automation (ICRA), 2012 IEEE International Conference on
Conference_Location :
Saint Paul, MN
Print_ISBN :
978-1-4673-1403-9
Electronic_ISBN :
1050-4729
DOI :
10.1109/ICRA.2012.6224732