Design of a low-cost unmanned surface vehicle for swarm robotics research in laboratory environments

Gregory, Calvin (2020) Design of a low-cost unmanned surface vehicle for swarm robotics research in laboratory environments. Masters thesis, Memorial University of Newfoundland.

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Swarm robotics is the study of groups of simple, typically inexpensive agents working collaboratively toward a common goal. Such systems offer several benefits over single-robot solutions: they are flexible, scalable, and robust to the failure of individual agents. The majority of existing work in this field has focused on robots operating in terrestrial environments but the benefits of swarm systems extend to applications in the marine domain as well. The current scarcity of marine robotics platforms suitable for swarm research is detrimental to progress in this field. Of the few that exist, no publicly available unmanned surface vehicles can operate in a laboratory environment; an indoor tank of water where the vessels, temperature, lighting, etc. can be observed and controlled at all times. Laboratory testing is a common intermediate step in the hardware validation of algorithms. This thesis details the design of the microUSV: a small, inexpensive, laboratory-based platform developed to fill this gap. The microUSV system was validated by performing laboratory testing of two algorithms: a waypoint-following controller and orbital retrieval. The waypoint-following controller was a simple PI controller implementation which corrects a vessel's speed and heading to seek predetermined goal positions. The orbital retrieval algorithm is a novel method for a swarm of unmanned surface vehicles to gather floating marine contaminants such as plastics. The vessels follow a circular path, orbiting around a central collection location and veer outwards to retrieve contaminants they detect outside the designated area. This method can potentially be used to cluster floating plastics together from a large region to facilitate cleanup.

Item Type: Thesis (Masters)
Item ID: 14838
Additional Information: Includes bibliographical references (pages 121-134).
Keywords: robotics, swarm, unmanned surface vehicle, boat, marine
Department(s): Engineering and Applied Science, Faculty of
Date: October 2020
Date Type: Submission
Digital Object Identifier (DOI):
Library of Congress Subject Heading: Robots--Design and construction; Robotics--Industrial applications.

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