Economics at your fingertips  

Mobile Robot Localization and Navigation in Artificial Intelligence: Survey

G. Nirmala (), S. Geetha () and S. Selvakumar ()
Additional contact information
G. Nirmala: Assistant Professor, Kamaraj College of Engineering and Technology, Virudhunagar, Tamil Nadu, India
S. Geetha: Professor, School of Computing Science and Engineering, VIT University- Chennai Campus, Chennai, Tamil Nadu, India
S. Selvakumar: Professor, G.K.M. College of Engineering and Technology, Chennai, Tamil Nadu, India

Computational Methods in Social Sciences (CMSS), 2016, vol. 4, issue 2, 12-22

Abstract: The potential applications for mobile robots are enormous. The mobile robots must quickly and robustly perform useful tasks in a previously unknown, dynamic and challenging environment. Mobile robot navigation plays a key role in all mobile robot activities and tasks such as path planning. Mobile robots are machines which navigate around their environment getting sensory information about that environment and performing actions dependent on this sensory information. Localization is basic to navigation. Various techniques have been described for estimating the orientation and positioning of a mobile robot. Navigation may be defined as the process of guiding the movement of intelligent vehicle systems from one location to another location with the support of various types of sensors to the different environments such as indoor, outdoor and other complex environments by using various navigation methods. This paper reviews the following mobile robot systems which are used in navigation for localization (1) Odometry (2) Magnetic compass (3) Active beacons (4) Global positioning system (5) Landmark navigation (6) Pattern matching, 12-22

Keywords: Mobile Robot; Navigation; Localization (search for similar items in EconPapers)
Date: 2016-12
References: View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) ... _issue_2_art.002.pdf First version, 2016 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Computational Methods in Social Sciences (CMSS) is currently edited by Bogdan Oancea

More articles in Computational Methods in Social Sciences (CMSS) from "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences Contact information at EDIRC.
Bibliographic data for series maintained by Stefan Ciucu ().

Page updated 2019-02-23
Handle: RePEc:ntu:ntcmss:vol4-iss2-16-12