A comparison of line extraction algorithms using 2D laser rangefinder for indoor mobile robotics
By Viet Nguyen, Agostino Martinelli, Nicola Tomatis, Roland Yves Siegwart. 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005
400 citations recorded by the source corpus.
This paper presents an experimental evaluation of different line extraction algorithms on 2D laser scans for indoor environment. Six popular algorithms in mobile robotics and computer vision are selected and tested. Experiments are performed on 100 real data scans collected in an office environment with a map size of 80m /spl times/ 50m. Several comparison criteria are proposed and discussed to highlight the advantages and drawbacks of each algorithm, including speed, complexity, correctness and precision. The results of the algorithms are compared with the ground truth using standard statistical methods.
Subfields: Aerospace Engineering, Environmental Engineering, Instrumentation
View Paper: https://www.semanticscholar.org/paper/ae07dae0ffd5df66e06b3cc24a1dec9b4796c2b1
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Citations in the corpus
- Clustering for point pattern data (2017, background): “Today, clustering is widely used in a host of application areas including genetics [5], medical imaging [6], market research [7], social network analysis [8], and mobile robotics [9].”
- EXTENDED RANSAC ALGORITHM FOR AUTOMATIC DETECTION OF BUILDING ROOF PLANES FROM LIDAR DATA (2008, neutral): “Its principle is well explained by (Fischler and Bolles, 1981; McGlone et al., 2004; Nguyen et al., 2005).”
- Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review (2016, background): “Experimental evaluations of different line extraction algorithms on laser scans for mobile robots in indoor environments are presented in [103,104].”