Taking navigation off your hands: enabling autopilot capabilities outside of USVs
Every year, uncrewed surface vessels (USVs) at the cutting-edge of technology become more capable platforms for hydrographic surveying, inching ever closer to the dream of true autonomous force multiplication. Although the fundamental purpose of these vessels is data collection itself, many of the recent advances relate to navigation and autonomy. Some of these advances in navigation and autonomy can be brought to vessels never designed to have such capabilities through a novel offboard autopilot approach.
In the worst cases, USVs have no automatic navigation capabilities, relying on continuous manual navigation using a remote control. Through a research partnership, Spatialnetics and the University of New Brunswick have developed an autopilot for vessels not outfitted initially with the capability that can be used without modifying the vessel’s hardware. Instead, minimal modifications are made to the shore station to allow all hardware and software to be located there, reducing complexity and allowing the vessel to continue delivering the same payload and battery performance while upgrading its capabilities, allowing better survey repeatability and minimizing the workload for shore operators.
Moving to an offboard advanced navigation and autonomy solution that can be implemented on nearly any USV allows any remotely controlled data collection platform to be integrated into further advances in navigation capabilities such as multi-vessel swarming. Although cutting-edge USVs are advancing rapidly,
older or less sophisticated vessels are still powerful data collection platforms for research and industry. By implementing a simple yet innovative solution to improve their autonomy, the capabilities of these vessels are augmented to allow them to continue to be an important tool for remote hydrographic operations.
Graham Christie
Graham Christie is a Master of Science in Engineering student in the Department of Geodesy and Geomatics Engineering at the University of New Brunswick. He is a member of the Ocean Mapping Group at UNB, and is a Certified Hydrographer (In Training) and an Engineer in Training in the Canadian province of New Brunswick. His studies focus on ocean mapping, specifically on developing low-cost or open-source options for increasing autonomy for uncrewed surface vessels.
Daniel Neville
Daniel Neville is a founding partner and managing director of Spatialnetics. He obtained a Bachelor of Computer Science from the University of New Brunswick and has held multiple roles throughout his career in the hydrospatial industry. Across these roles he has combined an interest for new technology with improving human interaction with automated systems.
Ian Church
Dr. Ian Church is an Associate Professor in the Department of Geodesy and Geomatics Engineering at the University of New Brunswick. He leads the Ocean Mapping Group at UNB, is the chair of the Canadian Ocean Mapping Research and Education Network (COMREN), and is a Professional Engineer in the province of New Brunswick. He specializes in ocean mapping research and training, with almost 20 years of experience in the field.
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept All”, you consent to the use of ALL the cookies. However, you may visit "Cookie Settings" to provide a controlled consent.
This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
Cookie
Duration
Description
cookielawinfo-checkbox-analytics
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional
11 months
The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy
11 months
The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.