Drones crash because of operator errors, hardware limitations, and a variety of other problems associated with an operating environment. A human operator may be able to detect and preemptively avoid a problem before it starts. The risk is very high that a drone will make mistakes and that its mistakes will be unique to its system. If the drone does not have enough intelligence to cover every case in which it is presented, it will not be suitable. Using simulations of package delivery may be able to reduce the limitations of drones and increase safety in the air and on the ground. The goals of this thesis are to describe computer-generated animation, image processing, flight control, and airspace monitoring. Further, lightweight simulation environments were used to investigate flight planning, flight-plan execution strategy, remote drone control, nearby air traffic, and flight restriction monitoring. A more resource intensive photo-realistic simulation environment was used to test hazard-detection and 3D-mapping. The tools presented in this research partly support the goal of autonomous drone package delivery, but additional testing is required to integrate these tools efficiently and then use them to train and safely operate a drone.
","abstract_html":"<p>Drones crash because of operator errors, hardware limitations, and a variety of other problems associated with an operating environment. A human operator may be able to detect and preemptively avoid a problem before it starts. The risk is very high that a drone will make mistakes and that its mistakes will be unique to its system. If the drone does not have enough intelligence to cover every case in which it is presented, it will not be suitable. Using simulations of package delivery may be able to reduce the limitations of drones and increase safety in the air and on the ground. The goals of this thesis are to describe computer-generated animation, image processing, flight control, and airspace monitoring. Further, lightweight simulation environments were used to investigate flight planning, flight-plan execution strategy, remote drone control, nearby air traffic, and flight restriction monitoring. A more resource intensive photo-realistic simulation environment was used to test hazard-detection and 3D-mapping. The tools presented in this research partly support the goal of autonomous drone package delivery, but additional testing is required to integrate these tools efficiently and then use them to train and safely operate a drone.</p>","abstract_has_math":false,"creators":["Chumbley, Kevin"],"institution":null,"degree_name":"Master of Science (MS) in Computer Science","degree_level":"Thesis: EWU Only","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-01-01T08:00:00Z","date_published":"2018-01-01T08:00:00Z","updated_at":"2026-07-24T02:12:33Z","subjects":["Computer Sciences"],"languages":[],"rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.ewu.edu/theses/538","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Chumbley, Kevin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis: EWU Only"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS) in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computer Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Access perpetually restricted to EWU users with an active EWU NetID"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.ewu.edu/theses/538"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Drones crash because of operator errors, hardware limitations, and a variety of other problems associated with an operating environment. A human operator may be able to detect and preemptively avoid a problem before it starts. The risk is very high that a drone will make mistakes and that its mistakes will be unique to its system. If the drone does not have enough intelligence to cover every case in which it is presented, it will not be suitable. Using simulations of package delivery may be able to reduce the limitations of drones and increase safety in the air and on the ground. The goals of this thesis are to describe computer-generated animation, image processing, flight control, and airspace monitoring. Further, lightweight simulation environments were used to investigate flight planning, flight-plan execution strategy, remote drone control, nearby air traffic, and flight restriction monitoring. A more resource intensive photo-realistic simulation environment was used to test hazard-detection and 3D-mapping. The tools presented in this research partly support the goal of autonomous drone package delivery, but additional testing is required to integrate these tools efficiently and then use them to train and safely operate a drone.
"]},{"key":"dc:title","label":"Title","values":["Improving Aerial Package Delivery Through Simulation of Hazard Detection, Mapping, and Regulatory Compliance"]}]}],"canonical_facts":{"dc:creator":["Chumbley, Kevin"],"dc:description.abstract":["Drones crash because of operator errors, hardware limitations, and a variety of other problems associated with an operating environment. A human operator may be able to detect and preemptively avoid a problem before it starts. The risk is very high that a drone will make mistakes and that its mistakes will be unique to its system. If the drone does not have enough intelligence to cover every case in which it is presented, it will not be suitable. Using simulations of package delivery may be able to reduce the limitations of drones and increase safety in the air and on the ground. The goals of this thesis are to describe computer-generated animation, image processing, flight control, and airspace monitoring. Further, lightweight simulation environments were used to investigate flight planning, flight-plan execution strategy, remote drone control, nearby air traffic, and flight restriction monitoring. A more resource intensive photo-realistic simulation environment was used to test hazard-detection and 3D-mapping. The tools presented in this research partly support the goal of autonomous drone package delivery, but additional testing is required to integrate these tools efficiently and then use them to train and safely operate a drone.
"],"dc:identifier":["https://dc.ewu.edu/theses/538"],"dc:rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"dc:subject":["Computer Sciences"],"dc:title":["Improving Aerial Package Delivery Through Simulation of Hazard Detection, Mapping, and Regulatory Compliance"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis: EWU Only"],"thesis:degree_name":["Master of Science (MS) in Computer Science"]},"updated_at":"2026-07-24T02:12:33Z"}