A Simple Integrative Solution For Simultaneous Localization And Mapping

Min Raj Nepali; Ashutosh; Dubey Aditya Housila Prasad; Susheel Balasubramaniah; Venkatesh EN

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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

Published in International Journal of Intelligent Systems and Applications in Robotics (IJRA)

Volume - 5 Issue - 2 | Publication Date - October 2014 Table of Contents

MORE INFORMATION

References | Abstracting & Indexing

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.

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REFERENCES

H. F. Durrant-Whyte, “Where am I? A Tutorial on Mobile Vehicle Localization,” Industrial Robot, vol. 21, no. 2, pp. 11±16, 1994.

J.A. Castellanos and J.D. Tard´os. “Mobile Robot Localization and Map Building: A Multisensor Fusion Approach”. Kluwer Academic Publishers, Boston, MA, 2000.

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.

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

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

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.

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.

S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents). The MIT Press, 2005.

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.

MANUSCRIPT AUTHORS

Mr. Min Raj Nepali