Autonomous Surface Sea Vessel Swarm Robotic Control Algorithm for Climate Forecasting

Developing intelligent control algorithms for fleets of autonomous surface vessels
water surface

Autonomous Surface Sea Vessel Swarm Robotic Control Algorithm for Climate Forecasting

Developing intelligent control algorithms for fleets of autonomous surface vessels
Title: Autonomous Surface Sea Vessel Swarm Robotic Control Algorithm for Climate Forecasting 
Dates: 2025-2029 
Project partners: Oshen Ltd 
University of Plymouth staff: Dr Dena Bazazian(PI), Dr Pablo Borja, Dr Nieves Valiente
 

Project objectives

The project aims to develop advanced swarm control and coordination algorithms that allow multiple autonomous surface vessels to work together efficiently in dynamic marine environments. Key objectives include enabling autonomous mission planning, adaptive navigation, distributed data collection, real-time communication between vessels, and energy-efficient operation over extended deployments. 
The project also seeks to optimise environmental sensing coverage, improve the quality and quantity of oceanographic data available for climate forecasting, and demonstrate how robotic swarms can provide a scalable and cost-effective alternative to traditional ocean monitoring methods. 
 

By enabling autonomous fleets of intelligent surface vessels to work cooperatively, this project aims to transform ocean observation and provide the high-quality environmental data needed for more accurate climate forecasting and sustainable management of our oceans.

Dena BazazianDr Dena Bazazian
Lecturer in Robotics and Machine Vision

 
Accurate climate forecasting relies heavily on comprehensive observations of the world's oceans, which play a fundamental role in regulating the Earth's climate through heat transport, carbon absorption, and atmospheric interactions. However, collecting oceanographic data at sufficient spatial and temporal scales remains a significant challenge due to the vast size of marine environments, harsh operating conditions, and the high cost of traditional monitoring platforms such as research vessels and fixed sensor networks. 
As climate change accelerates, there is an increasing demand for continuous, high-resolution environmental observations to improve predictive models, support scientific research, and inform environmental policy and decision-making. 
 

This project addresses these challenges by developing swarm robotic control algorithms for networks of autonomous surface vessels capable of operating collaboratively and with minimal human intervention. The vessels can autonomously distribute themselves across large areas, adaptively respond to changing environmental conditions, and coordinate sensing activities to maximise data coverage and collection efficiency. 
By providing persistent and scalable ocean monitoring capabilities, the swarm can deliver valuable measurements of key environmental variables such as temperature, salinity, currents, and atmospheric conditions. These data can be integrated into climate forecasting and environmental modelling systems, helping to improve forecast accuracy while reducing operational costs and expanding the reach of marine observation networks. 

Centre for Decarbonisation and Offshore Renewable Energy 

In response to climate change imperatives, we are bringing together a critical mass of leading research and expertise from across the University of Plymouth. Through co-creation and collaboration with partners from business, government and key communities from across the globe, the Centre aims to be a beacon for the University’s whole-system transdisciplinary approach to solutions-oriented research, accelerating sustainable developments in decarbonisation and renewable energy.
Centre for Decarbonisation and Offshore Renewable Energy