Collision Avoidance Using a Low-Cost Forward-Looking Sonar for Small AUVs

Simple item page
dc.contributor.authorMorency, Christopher Charlesen
dc.contributor.committeechairStilwell, Daniel J.en
dc.contributor.committeememberPatterson, Cameron D.en
dc.contributor.committeememberHaskell, Peter E.en
dc.contributor.committeememberWilliams, Ryan K.en
dc.contributor.committeememberWoolsey, Craig A.en
dc.contributor.departmentElectrical Engineeringen
dc.date.accessioned2024-04-17T16:32:11Zen
dc.date.available2024-04-17T16:32:11Zen
dc.date.issued2024-03-22en
dc.description.abstractIn this dissertation, we seek to improve collision avoidance for autonomous underwater vehicles (AUVs). More specifically, we consider the case of a small AUV using a forward-looking sonar system with a limited number of beams. We describe a high-fidelity sonar model and simulation environment that was developed to aid in the design of the sonar system. The simulator achieves real-time visualization through ray tracing and approximation, and can be used to assess sonar design choices, such as beam pattern and beam location, and to evaluate obstacle detection algorithms. We analyze the benefit of using a few beams instead of a single beam for a low-cost obstacle avoidance sonar for small AUVs. Single-beam systems are small and low-cost, while multi-beam sonar systems are more expensive and complex, often incorporating hundreds of beams. We want to quantify the improvement in obstacle avoidance performance of adding a few beams to a single-beam system. Furthermore, we developed a collision avoidance strategy specifically designed for the novel sonar system. The collision avoidance strategy is based on posterior expected loss, and explicitly couples obstacle detection, collision avoidance, and planning. We demonstrate the strategy with field trials using the 690 AUV, built by the Center for Marine Autonomy and Robotics at Virginia Tech, with a prototype forward-looking sonar comprising of nine beams.en
dc.description.abstractgeneralThis dissertation focuses on improving collision avoidance capabilities for small autonomous underwater vehicles (AUVs). Specifically, we are looking at the scenario of an AUV equipped with a forward-looking sonar system using only a few beams to detect obstacles in our environment. We develop a sophisticated sonar model and simulation environment to facilitate the design of the sonar system. Our simulator enables real-time visualization, offering insights into sonar design aspects. It also serves as a tool for evaluating obstacle detection algorithms. The research investigates the advantages of utilizing multiple beams compared to a single-beam system for a cost-effective obstacle avoidance solution for small AUVs. Single-beam sonar systems are small and affordable, while multi-beam sonar systems are more complex and expensive. The aim is to quantify the improvement in obstacle avoidance performance when adding additional sonar beams. Additionally, a collision avoidance strategy tailored to the novel sonar system is developed. This strategy, developed using a statistical model, integrates obstacle detection, collision avoidance, and planning. The effectiveness of the strategy is demonstrated through field trials using the 690 AUV, constructed by the Center for Marine Autonomy and Robotics at Virginia Tech, equipped with a prototype forward-looking sonar using nine beams.en
dc.description.degreeDoctor of Philosophyen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:39474en
dc.identifier.urihttps://hdl.handle.net/10919/118601en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectCollision Avoidanceen
dc.subjectMarine Roboticsen
dc.subjectAutonomous Underwater Vehiclesen
dc.subjectField Roboticsen
dc.subjectForward-Looking Sonaren
dc.subjectHigh-Fidelity Simulationsen
dc.titleCollision Avoidance Using a Low-Cost Forward-Looking Sonar for Small AUVsen
dc.typeDissertationen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.nameDoctor of Philosophyen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Morency_CC_D_2024.pdf
Size:
14.42 MB
Format:
Adobe Portable Document Format
Download

Collections

Doctoral Dissertations