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dc.contributor.authorKrawiec, Bryan Michaelen_US
dc.date.accessioned2014-03-14T20:36:11Z
dc.date.available2014-03-14T20:36:11Z
dc.date.issued2012-05-02en_US
dc.identifier.otheretd-05102012-121859en_US
dc.identifier.urihttp://hdl.handle.net/10919/32545
dc.description.abstractIn the event of a disaster, first responders must rapidly gain situational awareness about the environment in order to plan effective response operations. Unmanned ground vehicles are well suited for this task but often require a strong communication link to a remote ground station to effectively relay information. When considering an obstacle-rich environment, non-line-of-sight conditions and naive navigation strategies can cause substantial degradations in radio link quality. Therefore, this thesis incorporates an unmanned aerial vehicle as a radio repeating node and presents a path planning strategy to cooperatively navigate the vehicle team so that radio link health is maintained. This navigation technique is formulated as an A*-based search and this thesis presents the formulation of this path planner as well as an investigation into strategies that provide computational efficiency to the search process. The path planner uses predictions of radio signal health at different vehicle configurations to effectively navigate the vehicles and simulations have shown that the path planner produces favorable results in comparison to several conceivable naive radio repeating variants. The results also show that the radio repeating path planner has outperformed the naive variants in both simulated environments and in field testing where a Yamaha RMAX unmanned helicopter and a ground vehicle were used as the vehicle team. Since A* is a general search process, this thesis also presents a roadway detection algorithm using A* and edge detection image processing techniques. This algorithm can supplement unmanned vehicle operations and has shown favorable performance for images with well-defined roadways.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartKrawiec_BM_T_2012.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectA*en_US
dc.subjectRadio Repeatingen_US
dc.subjectPath Planningen_US
dc.subjectUAVen_US
dc.subjectRoadway Detectionen_US
dc.titleA*-Based Path Planning for an Unmanned Aerial and Ground Vehicle Team in a Radio Repeating Operationen_US
dc.typeThesisen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeechairKochersberger, Kevin Bruceen_US
dc.contributor.committeememberConner, David C.en_US
dc.contributor.committeememberFarhood, Mazenen_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05102012-121859/en_US
dc.date.sdate2012-05-10en_US
dc.date.rdate2012-05-30
dc.date.adate2012-05-30en_US


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