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Position fusion for an outdoor mobile robot

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dc.contributor.author Burke, Michael G
dc.contributor.author Sabatta, D
dc.date.accessioned 2009-12-08T11:08:13Z
dc.date.available 2009-12-08T11:08:13Z
dc.date.issued 2009-11
dc.identifier.citation Burke, M.G. and Sabatta, D. 2009. Position fusion for an outdoor mobile robot. 3rd Robotics and Mechatronics Symposium (ROBMECH 2009). Pretoria, South Africa, 8-10 November 2009, pp 5 en
dc.identifier.isbn 9780620447218
dc.identifier.uri http://hdl.handle.net/10204/3817
dc.description 3rd Robotics and Mechatronics Symposium (ROBMECH 2009). Pretoria, South Africa, 8-10 November 2009 en
dc.description.abstract Global Positioning Systems (GPS) provide an effective means of outdoor localisation. Unfortunately they are subject to a variety of errors, particularly in cluttered environments where GPS signal is not always available. Whilst GPS positional information includes measures of signal quality, these can not always be trusted, particularly just after a lost positional fix is regained. This paper presents the use of an Extended Kalman Filter to fuse GPS and odometric measurements, in order to improve vehicle positional and heading estimates. An odometric motion model is used to predict future positions, which are corrected by GPS measurements. Uncertainty in positional information from both GPS and odometry systems is modelled. The system has been implemented on Seekur, a terrestrial platform manufactured by Mobile Robots. Results of an experimental excursion of over 2 km are presented and show the efficacy of the system. en
dc.language.iso en en
dc.subject Global positioning systems en
dc.subject Odometry en
dc.subject Extended Kalman filter en
dc.subject Position fusion en
dc.subject Mobile robot en
dc.subject Seekur en
dc.subject Outdoor mobile robot en
dc.subject Robotics en
dc.title Position fusion for an outdoor mobile robot en
dc.type Conference Presentation en
dc.identifier.apacitation Burke, M. G., & Sabatta, D. (2009). Position fusion for an outdoor mobile robot. http://hdl.handle.net/10204/3817 en_ZA
dc.identifier.chicagocitation Burke, Michael G, and D Sabatta. "Position fusion for an outdoor mobile robot." (2009): http://hdl.handle.net/10204/3817 en_ZA
dc.identifier.vancouvercitation Burke MG, Sabatta D, Position fusion for an outdoor mobile robot; 2009. http://hdl.handle.net/10204/3817 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Burke, Michael G AU - Sabatta, D AB - Global Positioning Systems (GPS) provide an effective means of outdoor localisation. Unfortunately they are subject to a variety of errors, particularly in cluttered environments where GPS signal is not always available. Whilst GPS positional information includes measures of signal quality, these can not always be trusted, particularly just after a lost positional fix is regained. This paper presents the use of an Extended Kalman Filter to fuse GPS and odometric measurements, in order to improve vehicle positional and heading estimates. An odometric motion model is used to predict future positions, which are corrected by GPS measurements. Uncertainty in positional information from both GPS and odometry systems is modelled. The system has been implemented on Seekur, a terrestrial platform manufactured by Mobile Robots. Results of an experimental excursion of over 2 km are presented and show the efficacy of the system. DA - 2009-11 DB - ResearchSpace DP - CSIR KW - Global positioning systems KW - Odometry KW - Extended Kalman filter KW - Position fusion KW - Mobile robot KW - Seekur KW - Outdoor mobile robot KW - Robotics LK - https://researchspace.csir.co.za PY - 2009 SM - 9780620447218 T1 - Position fusion for an outdoor mobile robot TI - Position fusion for an outdoor mobile robot UR - http://hdl.handle.net/10204/3817 ER - en_ZA


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