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A*-Based Path Planning for an Unmanned Aerial and Ground Vehicle Team in a Radio Repeating Operation

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dc.contributor.authorKrawiec, Bryan Michaelen
dc.contributor.committeechairKochersberger, Kevin B.en
dc.contributor.committeememberConner, David C.en
dc.contributor.committeememberFarhood, Mazen H.en
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2014-03-14T20:36:11Zen
dc.date.adate2012-05-30en
dc.date.available2014-03-14T20:36:11Zen
dc.date.issued2012-05-02en
dc.date.rdate2012-05-30en
dc.date.sdate2012-05-10en
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
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-05102012-121859en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05102012-121859/en
dc.identifier.urihttp://hdl.handle.net/10919/32545en
dc.publisherVirginia Techen
dc.relation.haspartKrawiec_BM_T_2012.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectA*en
dc.subjectRadio Repeatingen
dc.subjectPath Planningen
dc.subjectDrone aircraften
dc.subjectRoadway Detectionen
dc.titleA*-Based Path Planning for an Unmanned Aerial and Ground Vehicle Team in a Radio Repeating Operationen
dc.typeThesisen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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