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dc.contributor.advisorJonathan How, Matthew Stoeckle and Louis Breger.en_US
dc.contributor.authorLe Floch, Brian (Brian Henri)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Aeronautics and Astronautics.en_US
dc.date.accessioned2017-12-05T19:14:07Z
dc.date.available2017-12-05T19:14:07Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/112467
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 79-81).en_US
dc.description.abstractAerial resupply can deliver cargo to locations across the globe. A challenge for modern guided parafoil systems is to land accurately in complex terrain, including canyons and cities. This thesis presents the Rewire-RRT algorithm for parafoil terminal guidance. The algorithm uses Rapidly-Exploring Random Trees (RRT) to efficiently search for feasible paths through complex environments. Most importantly, Rewire-RRT provides a mechanism to build and rewire the tree to explicitly minimize the risk of collision with obstacles along each path and to minimize the expected final miss distance from the target. This key adaptation allows for parafoil guidance in urban drop zones not previously considered for airdrop operations. The Rewire-RRT algorithm is first developed and tested in two dimensions and demonstrated to have greater performance than RRT for simple dynamical systems, finding paths that are shorter and safer than those found by RRT. Then, Rewire-RRT is shown to be an effective path planner for a guided parafoil with complex dynamics. Paths planned by Rewire-RRT better meet the performance objectives of guided parafoils than those planned by RRT. Finally, simulation results show that Rewire-RRT performs better than state-of- the-art terminal guidance strategies for guided parafoils when the target location is cluttered with multiple three-dimensional obstacles.en_US
dc.description.statementofresponsibilityby Brian Le Floch.en_US
dc.format.extent81 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectAeronautics and Astronautics.en_US
dc.titleSampling-based path planner for guided airdrop in urban environmentsen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
dc.identifier.oclc1011039415en_US


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