{"id":{"repo_id":"unlv","oai_identifier":"oai:oasis.library.unlv.edu:rtds-2560"},"canonical_url":"https://search.dev.ndltd.org/etd/unlv/oai:oasis.library.unlv.edu:rtds-2560","repository":{"repo_id":"unlv","name":"University of Nevada - Las Vegas","base_url":"https://oasis.library.unlv.edu/do/oai/"},"display":{"title":"Trajectory planning in the presence of risk regions","abstract":"We consider the problem of developing fast algorithms for computing short collision-free paths for aerial vehicles in the presence of obstacles and enemy radar installations. When aerial vehicles are deployed in such regions, it is critical to compute admissible paths having reduced exposure to threats. The generalized version of this problem is known to be NP-hard [4]. We consider simplified versions in two dimensions. One of the specific problems we address is to adjust a given k-legged trajectory to reduce exposure to threats. We also propose an algorithm to compute a k-legged risk-reduced path using a stage graph which runs in 0(m 2p) time where m is the number of vertices per turn region and p is the number of radar and obstacle polygon edges. In addition, we describe methods for obtaining multiple risk-reduced paths and node disjoint paths from the stage graph. We also discuss the implementation of the proposed algorithms.","abstract_html":"We consider the problem of developing fast algorithms for computing short collision-free paths for aerial vehicles in the presence of obstacles and enemy radar installations. When aerial vehicles are deployed in such regions, it is critical to compute admissible paths having reduced exposure to threats. The generalized version of this problem is known to be NP-hard [4]. We consider simplified versions in two dimensions. One of the specific problems we address is to adjust a given k-legged trajectory to reduce exposure to threats. We also propose an algorithm to compute a k-legged risk-reduced path using a stage graph which runs in 0(m 2p) time where m is the number of vertices per turn region and p is the number of radar and obstacle polygon edges. In addition, we describe methods for obtaining multiple risk-reduced paths and node disjoint paths from the stage graph. We also discuss the implementation of the proposed algorithms.","abstract_has_math":false,"creators":["Sherwood, Michael Allan"],"institution":"University of Nevada, Las Vegas","degree_name":"Master of Science (MS)","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Laxmi P. Gewali"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2003,"date_issued":"2003-01-01T08:00:00Z","date_published":"2003-01-01T08:00:00Z","updated_at":"2026-07-24T05:25:40Z","subjects":[],"languages":["English"],"rights":["IN COPYRIGHT. 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One of the specific problems we address is to adjust a given k-legged trajectory to reduce exposure to threats. We also propose an algorithm to compute a k-legged risk-reduced path using a stage graph which runs in 0(m 2p) time where m is the number of vertices per turn region and p is the number of radar and obstacle polygon edges. In addition, we describe methods for obtaining multiple risk-reduced paths and node disjoint paths from the stage graph. We also discuss the implementation of the proposed algorithms."]},{"key":"dc:format","label":"Dc Format","values":["pdf"]},{"key":"dc:title","label":"Title","values":["Trajectory planning in the presence of risk regions"]}]}],"canonical_facts":{"dc:contributor":["Laxmi P. Gewali"],"dc:creator":["Sherwood, Michael Allan"],"dc:description.abstract":["We consider the problem of developing fast algorithms for computing short collision-free paths for aerial vehicles in the presence of obstacles and enemy radar installations. When aerial vehicles are deployed in such regions, it is critical to compute admissible paths having reduced exposure to threats. The generalized version of this problem is known to be NP-hard [4]. We consider simplified versions in two dimensions. One of the specific problems we address is to adjust a given k-legged trajectory to reduce exposure to threats. We also propose an algorithm to compute a k-legged risk-reduced path using a stage graph which runs in 0(m 2p) time where m is the number of vertices per turn region and p is the number of radar and obstacle polygon edges. In addition, we describe methods for obtaining multiple risk-reduced paths and node disjoint paths from the stage graph. 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