We are experiencing issues opening hdl.handle.net links on ANU campus. If you are experiencing issues, please contact the repository team repository.admin@anu.edu.au for assistance.
 

The Convergence Property of Goal-based Visual Navigation

dc.contributor.authorBianco, Giovanni
dc.contributor.authorZelinsky, Alex
dc.coverage.spatialLausanne Switzerland
dc.date.accessioned2015-12-13T23:23:53Z
dc.date.available2015-12-13T23:23:53Z
dc.date.createdSeptember 30 2002
dc.date.issued2002
dc.date.updated2015-12-12T09:18:04Z
dc.description.abstractThe use of landmarks is a natural and instinctive method to determine the whereabouts of a location or a means to proceed to a particular location. Results provided in this paper indicate that landmark-based navigation possesses a corrective or feedback trait that produces a convergence bound on the movements to the goal position, in contrast to the odometry-based movements, which leads to the drift between successive navigation movements. Experiments show that the vector field approach can be used to explain the convergence property of landmark-based guidance tasks. Experiments have been carried out operating with a Nomad mobile robot equipped with real-time visual landmark tracking system.
dc.identifier.isbn0780373987
dc.identifier.urihttp://hdl.handle.net/1885/91965
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2002)
dc.sourceProceedings of the 2002 IEEE/ RSJ International Conference on Intelligent Robots and Systems
dc.subjectKeywords: Computer vision; Convergence of numerical methods; Mathematical models; Motion planning; Navigation; Sensor data fusion; Goal-based visual navigation; Odometry; Real-time visual landmark tracking system; Mobile robots
dc.titleThe Convergence Property of Goal-based Visual Navigation
dc.typeConference paper
local.bibliographicCitation.lastpage654
local.bibliographicCitation.startpage649
local.contributor.affiliationBianco, Giovanni, Universita di Verona
local.contributor.affiliationZelinsky, Alex, College of Engineering and Computer Science, ANU
local.contributor.authoruidZelinsky, Alex, u9615131
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080101 - Adaptive Agents and Intelligent Robotics
local.identifier.ariespublicationMigratedxPub22902
local.identifier.scopusID2-s2.0-0036450927
local.type.statusPublished Version

Downloads

Back to topicon-arrow-up-solid
 
APRU
IARU
 
edX
Group of Eight Member

Acknowledgement of Country

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.


Contact ANUCopyrightDisclaimerPrivacyFreedom of Information

+61 2 6125 5111 The Australian National University, Canberra

TEQSA Provider ID: PRV12002 (Australian University) CRICOS Provider Code: 00120C ABN: 52 234 063 906