Date of Award

1-1-2016

Document Type

Masters Thesis

Degree Name

M.S.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science

First Advisor

Kyoung-Dae Kim, Ph.D.

Second Advisor

Ali Besharat

Third Advisor

Kimon Valavanis

Keywords

Artificial potential function, Autonomy, Collision avoidance, Quadrotor, Teleoperation, Unmanned aerial vehicle

Abstract

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.

Copyright Date

January 2016

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Mohammed Salim Qasim

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

82 p.

Discipline

Electrical Engineering, Mechanical Engineering, Computer Engineering

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