DocumentCode :
414171
Title :
Pose invariant, robust feature extraction from data with a modified scale space approach
Author :
Fan Tang ; Adams, Martin ; Ibanez-Guzman, Javier ; Wijesoma, W.S.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume :
3
fYear :
2004
fDate :
26 April-1 May 2004
Firstpage :
3173
Abstract :
Feature-based simultaneous localization and map building (SLAM) approaches require a robust method to extract position invariant landmarks from the surrounding environment. 2D laser range finders are currently one of the most common sensors used to obtain environmental information for mobile robot navigation due to their reliability, accuracy and low cost. However, the 2D laser scan data only give very limited information, making it difficult to extract meaningful features particularly in unstructured environments. The most important steps to extract features are segmentation and noise reduction. Scale space and adaptive smoothing are two common techniques within the vision community. They are used to remove high frequency noise and represent image data in multi-scale spaces. They allow for an easier segmentation of images and the extraction of features in the appropriate scale. In this paper, a modified adaptive smoothing algorithm is proposed and applied to laser range data within a modified scale space framework. This algorithm smoothes range data and segments it at the same time by translating a line model mask over the range data. Lines can be extracted from the segments by using a standard fitting algorithm.
Keywords :
adaptive filters; feature extraction; image representation; image segmentation; laser ranging; mobile robots; navigation; robot vision; SLAM; feature-based simultaneous localization and map building; fitting algorithm; high frequency noise removal; image data representation; image segmentation; laser range data; line model mask translation; lines extraction; mobile robot navigation; modified adaptive smoothing algorithm; modified scale space framework; multi-scale spaces; pose invariance; position invariant landmark extraction; robust feature extraction; Costs; Data mining; Feature extraction; Image segmentation; Laser noise; Mobile robots; Navigation; Robustness; Simultaneous localization and mapping; Smoothing methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
ISSN :
1050-4729
Print_ISBN :
0-7803-8232-3
Type :
conf
DOI :
10.1109/ROBOT.2004.1307551
Filename :
1307551
Link To Document :
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