Toward Tactical Autonomy in Aerial Robotics

dc.contributor.advisorL'Afflitto, Andrea
dc.contributor.authorKarinshak, Joshua
dc.contributor.committeeMemberSun, Wei
dc.contributor.committeeMemberTang, Choon Yik
dc.date.accessioned2019-07-01T15:43:34Z
dc.date.available2019-07-01T15:43:34Z
dc.date.issued2019-08-01
dc.date.manuscript2019-06-15
dc.description.abstractThis thesis addresses the issue of the generation of tactical trajectories, as is desirable in the case of robot autonomy in hostile environments. The generation of such trajectory currently lies beyond the purview of contemporary path planning research, which focuses on solutions to the shortest path problem and variations thereof. This novel guidance system is developed as a two-stage process. In the first stage, a graph-based search algorithm is used to generate a global trajectory, as is the norm for state-of-the-art path planners. In the second stage, optimal control techniques are utilized to develop local trajectories that are optimal with respect to user-defined cost matrices over a finite time horizon. The guidance system is implemented for use with quadrotor vehicles. It is tested in simulation and then in flight. In both cases, the trajectory generated by the system makes use of cover present in the environment, rather than fly directly to the goal point. Additionally included is a discussion on modern visual navigation techniques, which, if implemented, would enable autonomous operation in initially unknown environments. In combination with the guidance algorithm developed in this thesis, the resulting system would be fully capable of conducting missions in hostile environmentsen_US
dc.identifier.urihttps://hdl.handle.net/11244/320366
dc.languageenen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectmodel predictive controlen_US
dc.subjectpath planningen_US
dc.subjectautonomyen_US
dc.subjectquadrotoren_US
dc.thesis.degreeMaster of Scienceen_US
dc.titleToward Tactical Autonomy in Aerial Roboticsen_US
ou.groupGallogly College of Engineering::School of Aerospace and Mechanical Engineeringen_US
shareok.nativefileaccessrestricteden_US

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