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.

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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