dc.contributor.author | Ssebazza, Leslie | |
dc.date.accessioned | 2011-08-25T14:09:18Z | |
dc.date.available | 2011-08-25T14:09:18Z | |
dc.date.issued | 2011-08-25 | |
dc.identifier.uri | http://hdl.handle.net/10222/14116 | |
dc.description.abstract | Differential Global Positioning System (dGPS) sensors provide a way for an outdoor
wheeled mobile robot to achieve better localization that results in improved navigation
and control of outdoor Wheeled Mobile Robots (WMR). This thesis proposes
an approach for path following of outdoor WMR. The primary focus of the approach
is to use dGPS technology as the only sensing device for localization. Filter estimation
techniques are also considered to account for measurement inaccuracies. The
Extended Kalman Filter (EKF) is chosen and implemented as part of this approach
for improved results. A secondary focus of the approach, is to incorporate a modified
Potential Field Path Planning (PFPP) as an integral part of the proposed technique.
The dGPS-based proposed path following approach is first simulated in the simulation
environment. After which, it is applied and tested on a WMR experimental platform
for a set of experimental cases. | en_US |
dc.language.iso | en | en_US |
dc.title | DGPS-BASED LOCALIZATION FOR PATH FOLLOWING OF OUTDOOR WHEELED MOBILE ROBOTS | en_US |
dc.date.defence | 2011-07-25 | |
dc.contributor.department | Department of Mechanical Engineering | en_US |
dc.contributor.degree | Master of Applied Science | en_US |
dc.contributor.external-examiner | Dr. Jason Gu | en_US |
dc.contributor.graduate-coordinator | Dr. Alex Kalamkarov | en_US |
dc.contributor.thesis-reader | Dr. Ted Hubbard | en_US |
dc.contributor.thesis-supervisor | Dr. Ya-Jun Pan | en_US |
dc.contributor.ethics-approval | Not Applicable | en_US |
dc.contributor.manuscripts | Not Applicable | en_US |
dc.contributor.copyright-release | Not Applicable | en_US |