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Jonathan How, Matthew Stoeckle and Louis Breger. Le Floch, Brian (Brian Henri) Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics 2017-12-05T19:14:07Z 2017-12-05T19:14:07Z 2017 2017 http://hdl.handle.net/1721.1/112467 1011039415 Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 79-81). Aerial 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. by Brian Le Floch. S.M. 81 pages eng Massachusetts Institute of Technology MIT 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. http://dspace.mit.edu/handle/1721.1/7582 Aeronautics and Astronautics. Sampling-based path planner for guided airdrop in urban environments Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="fef6d90a-42e8-4357-abea-de00692da4ef"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Sampling-based path planner for guided airdrop in urban environments</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2017</PublicationDate> <Authors> <Author> <DisplayName>Le Floch, Brian (Brian Henri)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Aeronautics and Astronautics.</Keyword> <Abstract>Aerial 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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>