By Topic

Quantitative and qualitative comparison of three laser-range mapping algorithms using two types of laser scanner data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Scott, A. ; DePauw Univ., Greencastle, IN, USA ; Parker, L.E. ; Touzet, C.

Presents our initial results in comparing three algorithms for autonomous robotic mapping using two types of laser scanner data. The algorithms compared are the Markov localization approach of S. Thrun et al. (1998), F. Lu and E. Milios's (1997) iterative dual correspondence algorithm, and C. Touzet's (2000) model-free landmark extraction algorithm. The two types of laser scanner data utilized are the AccuRange laser scanner from Acuity and the SICK laser scanner. We compare these algorithms in terms of the quality of mapped results, computational requirements, and sensitivity to data and odometry errors. While the complete comparison of these algorithms on all these measures is not yet accomplished, our results to date indicate that laser mapping algorithms are not immediately transferrable from one type of laser scanner data to another. Instead, algorithms appear to make implicit assumptions on the quality or content of laser data that play a strong role in the quality of the mapping results

Published in:

Systems, Man, and Cybernetics, 2000 IEEE International Conference on  (Volume:2 )

Date of Conference:

2000