NDLI: A hybrid approach to RBPF based SLAM with grid mapping enhanced by line matching

Content Provider	IEEE Xplore Digital Library
Author	Wei-Jen Kuo Shih-Huan Tseng Jia-Yuan Yu Li-Chen Fu
Copyright Year	2009
Description	Author affiliation: Department of Computer Science and Engineering, National Taiwan University, Taiwan (Wei-Jen Kuo; Shih-Huan Tseng; Jia-Yuan Yu) \|\| Department. of Computer Science and Engineering and Department of Electrical Engineering, National Taiwan University, Taiwan (Li-Chen Fu)
Abstract	In this paper, we present a novel data structure representing the environment with occupancy grid cells while each grid map is associated with a set of line features extracted from laser scan points. Due to the fact that line segments are principal elements of artificial environments, they provide considerable geometric information about the environment which can be used for enhancing the accuracy of localization. Orthogonal characteristic of line features is the key issue to guarantee the consistency of the SLAM algorithm by allowing us to deal with lines that are parallel or perpendicular to each other. This behavior allows us to sample robot poses more correctly. As a result, the proposed algorithm can close bigger loops with the same number of particles. Experimental results are carried out using SICK LMS-100 laser scanner which has a maximum range of 20m and Pioneer 3DX mobile robot mapping an indoor environment with the size of 40m × 47m.
Starting Page	1523
Ending Page	1528
File Size	273045
Page Count	6
File Format	PDF
ISBN	9781424438037
DOI	10.1109/IROS.2009.5354214
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Simultaneous localization and mapping Indoor environments Computer science Mobile robots Databases Particle filters Data structures Data mining Orbital robotics Trajectory
Content Type	Text
Resource Type	Article

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