This thesis presents the design of a super-ellipsoidal potential function (SEPF) that can be used, in a static and dynamic environment, for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of the SEPF, we have the full control over the shape and size of the potential function. In our proposed approach, a teleoperated UAV can not only autonomously avoid collision with surrounding objects but also track the operator' control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAV collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation using virtual robot experimentation platform (v-rep) and Matlab programs and experimentation using a physical quadrotor UAV in a laboratory environment.
","abstract_html":"<p>This thesis presents the design of a super-ellipsoidal potential function (SEPF) that can be used, in a static and dynamic environment, for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of the SEPF, we have the full control over the shape and size of the potential function. In our proposed approach, a teleoperated UAV can not only autonomously avoid collision with surrounding objects but also track the operator' control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAV collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation using virtual robot experimentation platform (v-rep) and Matlab programs and experimentation using a physical quadrotor UAV in a laboratory environment.</p>","abstract_has_math":false,"creators":["Qasim, Mohammed Salim"],"institution":null,"degree_name":"M.S.","degree_level":"Masters Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kyoung-Dae Kim, Ph.D.","Ali Besharat","Kimon Valavanis"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-01-01T08:00:00Z","date_published":"2016-01-01T08:00:00Z","updated_at":"2026-07-24T02:02:03Z","subjects":["Artificial potential function","Autonomy","Collision avoidance","Quadrotor","Teleoperation","Unmanned aerial vehicle","Electrical and Computer Engineering"],"languages":["en"],"rights":["Copyright is held by the author. User is responsible for all copyright compliance.
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"],"dc:subject":["Artificial potential function","Autonomy","Collision avoidance","Quadrotor","Teleoperation","Unmanned aerial vehicle","Electrical and Computer Engineering"],"dc:title":["Autonomous Collision Avoidance for a Teleoperated UAV Based on a Super-Ellipsoidal Potential Function"],"thesis:degree_level":["Masters Thesis"],"thesis:degree_name":["M.S."]},"updated_at":"2026-07-24T02:02:03Z"}