Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

(577.31KB)
This is an Open Access publication published under CSC-OpenAccess Policy.
A Simple Integrative Solution For Simultaneous Localization And Mapping
Min Raj Nepali, Ashutosh, Dubey Aditya Housila Prasad, Susheel Balasubramaniah, Venkatesh EN
Pages - 24 - 35     |    Revised - 10-09-2014     |    Published - 10-10-2014
Volume - 5   Issue - 2    |    Publication Date - October 2014  Table of Contents
MORE INFORMATION
KEYWORDS
Localization, LRF, Feature Based Mapping, Odometry, SLAM, Split and Merge.
ABSTRACT
Simultaneous Localization and Mapping is a method used to find the location of a mobile robot while at the same time build a constructive map of its surrounding environment. This paper gives a brief description about a simple integrative SLAM technique using a Laser Range Finder (LRF) and Odometry data, primarily for indoor environments. In this project, a solution for the SLAM problem was implemented on a differential drive mobile robot equipped with a SICK laser scanner.
CITED BY (0)  
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PdfSR
1 H. F. Durrant-Whyte, “Where am I? A Tutorial on Mobile Vehicle Localization,” Industrial Robot, vol. 21, no. 2, pp. 11±16, 1994.
2 M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit. “FastSLAM: A factored solution to the simultaneous localization and mapping problem”. AAAI National Conference on Artificial Intelligence, pages 593–598, 2002.
3 S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents). The MIT Press, 2005.
4 Lina M. Paz, Pedro Pini´es, Juan D. Tard´os, and Jos´eNeira, Large- Scale 6-DOF SLAM With Stereo-in-Hand, IEEE Transactions On Robotics, Vol. 24, No. 5, October 2008
5 J.A. Castellanos and J.D. Tard´os. “Mobile Robot Localization and Map Building: A Multisensor Fusion Approach”. Kluwer Academic Publishers, Boston, MA, 2000.
6 W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonarbased mapping with mobile robots using EM. In Proc. 16th International Conf. on Machine Learning, pages 67–76. Morgan Kaufmann, San Francisco, CA, 1999.
7 S. Thrun, D. Fox, and W. Burgard, “A probabilistic approach to concurrent mapping and localization for mobile robots,” Machine Learning 31, 29–53 and Autonomous Robots 5, 253–271,(joint issue), 1998.
8 Jose Guivant, Eduardo Nebot and Stephan Baiker. “Autonomous Navigation and Map building Using Laser Range Sensors in Outdoor Applications”. Journal of Robotic Systems, Volume 17, No 10, October 2000
9 Jaun D. Tardos , Jose Neira , Paul M. Newman , John J. Leonard “Robust Mapping and Localization in Indoor Environments using Sonar Data.” The International Journal of Robotics Research Vol. 21, No. 4, April 2002.
Mr. Min Raj Nepali
Nitte Meenakshi Institute of Technology - India
nminraj92@gmail.com
Mr. Ashutosh
Nitte Meenakshi Institute of Technology - India
Mr. Dubey Aditya Housila Prasad
Nitte Meenakshi Institute of Technology - India
Mr. Susheel Balasubramaniah
Nitte Meenakshi Institute of Technology - India
Mr. Venkatesh EN
Nitte Meenakshi Institute of Technology - India