Publication:
USE OF ARTIFICIAL FIDUCIAL MARKERS FOR USV SWARM COORDINATION

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Authors
Heubach, Matthew J.
Subjects
controls
autonomy
swarm
Advisors
Bingham, Brian S.
Date of Issue
2022-12
Date
Publisher
Monterey, CA; Naval Postgraduate School
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Abstract
Typical swarm algorithms (leader-follower, artificial potentials, etc.) rely on knowledge about the pose of each vehicle and inter-vehicle proximity. This information is often obtained via Global Positioning System (GPS) and communicated via radio-frequency means.. This research examines the capabilities and limitations of using a fiducial marker system in conjunction with an artificial potential field algorithm to achieve inter-vehicle localization and coordinate the motion of unmanned surface vessels operating together in an environment where satellite and radio communications are inhibited. Using Gazebo, a physics-based robotic simulation environment, a virtual model is developed for incorporating fiducial markers on a group of autonomous surface vessels. A control framework using MATLAB and the Robot Operating System (ROS) is developed that integrates image processing, AprilTag fiducial marker detection, and artificial potential control algorithms. This architecture receives multiple video streams, detects AprilTags, and extracts pose information to control the forward motion and inter-vehicle spacing in a swarm of autonomous surface vessels. This control architecture is tested for a variety of trajectories and tuned so that the swarm can successfully maintain formation control.
Type
Thesis
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Department
Mechanical and Aerospace Engineering (MAE)
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Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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