In this thesis, a formation flight architecture is described along with the implementation and evaluation of a state-of-the-art vision-based algorithm for solving the problem of estimating and tracking a leader vehicle within a close-formation configuration. A vision-based algorithm that uses Darknet architecture and a formation flight control law to track and follow a leader with desired clearance in forward, lateral directions are developed and implemented. The architecture is run on a flight computer that handles the process in real-time while integrating navigation sensors and a stereo camera. Numerical simulations along with indoor and outdoor actual flight tests demonstrate the capabilities of detection and tracking by providing a low cost, compact size and low weight solution for the problem of estimating the location of other cooperative or non-cooperative flying vehicles within a formation architecture.
","abstract_html":"<p>In this thesis, a formation flight architecture is described along with the implementation and evaluation of a state-of-the-art vision-based algorithm for solving the problem of estimating and tracking a leader vehicle within a close-formation configuration. A vision-based algorithm that uses Darknet architecture and a formation flight control law to track and follow a leader with desired clearance in forward, lateral directions are developed and implemented. The architecture is run on a flight computer that handles the process in real-time while integrating navigation sensors and a stereo camera. Numerical simulations along with indoor and outdoor actual flight tests demonstrate the capabilities of detection and tracking by providing a low cost, compact size and low weight solution for the problem of estimating the location of other cooperative or non-cooperative flying vehicles within a formation architecture.</p>","abstract_has_math":false,"creators":["Irigireddy, Ashok Sarath Chandra Reddy"],"institution":null,"degree_name":"Master of Science in Unmanned and Autonomous Systems Engineering","degree_level":"Thesis - Open Access","degree_discipline":"Electrical, Computer, Software, and Systems Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-01-03T08:00:00Z","date_published":"2020-01-03T08:00:00Z","updated_at":"2026-07-27T19:25:29Z","subjects":["close formation","vision-based","position detection","Aerospace Engineering","Electrical and Computer Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/499","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Irigireddy, Ashok Sarath Chandra Reddy"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical, Computer, Software, and Systems Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Unmanned and Autonomous Systems Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["close formation","vision-based","position detection","Aerospace Engineering","Electrical and Computer Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/499"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In this thesis, a formation flight architecture is described along with the implementation and evaluation of a state-of-the-art vision-based algorithm for solving the problem of estimating and tracking a leader vehicle within a close-formation configuration. A vision-based algorithm that uses Darknet architecture and a formation flight control law to track and follow a leader with desired clearance in forward, lateral directions are developed and implemented. The architecture is run on a flight computer that handles the process in real-time while integrating navigation sensors and a stereo camera. Numerical simulations along with indoor and outdoor actual flight tests demonstrate the capabilities of detection and tracking by providing a low cost, compact size and low weight solution for the problem of estimating the location of other cooperative or non-cooperative flying vehicles within a formation architecture.
"]},{"key":"dc:title","label":"Title","values":["Close Formation Flight Missions Using Vision-Based Position Detection System"]}]}],"canonical_facts":{"dc:creator":["Irigireddy, Ashok Sarath Chandra Reddy"],"dc:description.abstract":["In this thesis, a formation flight architecture is described along with the implementation and evaluation of a state-of-the-art vision-based algorithm for solving the problem of estimating and tracking a leader vehicle within a close-formation configuration. A vision-based algorithm that uses Darknet architecture and a formation flight control law to track and follow a leader with desired clearance in forward, lateral directions are developed and implemented. The architecture is run on a flight computer that handles the process in real-time while integrating navigation sensors and a stereo camera. Numerical simulations along with indoor and outdoor actual flight tests demonstrate the capabilities of detection and tracking by providing a low cost, compact size and low weight solution for the problem of estimating the location of other cooperative or non-cooperative flying vehicles within a formation architecture.
"],"dc:identifier":["https://commons.erau.edu/edt/499"],"dc:subject":["close formation","vision-based","position detection","Aerospace Engineering","Electrical and Computer Engineering"],"dc:title":["Close Formation Flight Missions Using Vision-Based Position Detection System"],"thesis:degree_discipline":["Electrical, Computer, Software, and Systems Engineering"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Unmanned and Autonomous Systems Engineering"]},"updated_at":"2026-07-27T19:25:29Z"}