It took only a few decades for robotic underwater, surface and air vehicles to revolutionize ocean exploration. But this is just the beginning. Vehicle heterogeneity and functional diversity will enable new concepts of operation that could have not been imagined before. These include long endurance Atlantic operations to be undertaken by Autonomous Surface Vehicles (ASV).
The AutoNaut is a self-powered ASV developed by MOST (Autonomous Vessel) Ltd (https://www.autonautusv.com/). The ASV is designed to be a cost-effective, low manpower data collection platform, with zero-emission, extreme persistence, and the capability of surviving extreme weather conditions. Zero-emission is achieved solely by wave and solar power. A patented Wave-propulsion Technology converts energy from the pitch and roll of the waves. The AutoNaut is equipped with spring-loaded foils attached to the struts under the keel. These foils exploit the wave-induced vessel motion, caused by waves lifting the vessel, out of the water, and dropping it down again, to generate the forward propulsion speed in the order of 1-2 knots.
The main goal of this project is to develop a planning and execution control framework for long endurance operations to be performed by the AutoNaut with the goal of maximizing the scientific return of these operations while minimizing the logistical support. The candidate will explore AI-based systems, as well as other optimization and machine learning techniques, to develop an onboard trajectory optimization and execution framework on different ocean spatial and temporal scales. The onboard framework will be complemented by an onshore system incorporating forecasted wave and meteo data or observations.
The project builds on the experience of LSTS-UPORTO (https://lsts.fe.up.pt/) in the development and deployment of networked vehicle systems for ocean observation (https://schmidtocean.org/cruise/exploring_fronts_with_multiple_aerial-surface-underwater-vehicles). The proposed developments are applicable to other applications including autonomous ships.
Notice of the call
Download english version here
Tasks and Responsibilities:
- Familiarize yourself with the current state-of-the-art in the fields of (1) Vehicle motion planning, (2) Artificial Intelligence (AI) based planning systems, (3) observation of dynamic features of the ocean, (4) AI-based learning of dynamic features of the ocean using physics-based models and remote sensing data, (5) software frameworks for uncrewed maritime vehicles, including the LSTS software toolchain (https://www.lsts.pt/toolchain).
- Study the model and operational limitations of the AutoNaut ASV.
- Develop a robust optimal trajectory planning and execution control for the Autonaut with several levels of time-space granularities.
- Evaluate and test the planning and execution control framework in a simulation environment (LSTS toolchain) that high fidelity models of meteo-ocean conditions of the Atlantic Ocean.
- Deploy the planning and execution control framework on an Autonaut ASV for field testing in the Atlantic.
Prerequisites: Candidate must hold a master’s degree (or equivalent) in any of the following fields: computer science, mechanical/electrical engineering, physics, mathematics, marine sciences, or related fields. The degree should have been completed in the last 5 years at most (candidates completing and defending their MSc thesis by July 2021, are welcome). The candidate must have strong analytical skills and be able to work at the intersection of science and technology. The candidate should have experience in one of the following programming languages C/C++ and Python. Experience with robotic operations and/or with the Robot Operating System (ROS) or with the LSTS software toolchain is a plus. Proficiency in written and spoken English is also required.
Hiring institution specific remarks Due to local regulations the University of Porto position is for 48 months
Hiring institution University of Porto;
PhD Enrollment PhD position at the Laboratório de Sistemas e Tecnologias Subaquática – LSTS (Underwater Systems and Technologies Lab) at University of Porto (https://lsts.fe.up.pt/). The project involves collaboration with the +Atlantic Colab.
Main Academic Supervisor Prof. João Sousa (LSTS-UPorto), contact: email@example.com Co-supervisors: Dr. Renato Mendes (+Atlantic Colab and LSTS-UPorto) and Prof. Pierre Lermusiaux (MIT).
The AIR Centre PhD Scholarship Programme aims at training the leaders of the future
Enhancing scientific research and technology development capabilities of AIR Centre Network in order to better respond to national priorities and global challenges in the Atlantic region;
- Strengthening existing collaboration ties and exploring or developing new collaboration ties between the AIR Centre and the Portuguese scientific community in areas of common interest;
- Promoting bilateral/multilateral cooperation between Portuguese scientific institutions and other institutions from diverse Atlantic countries through inclusive knowledge and data sharing to promote job creation, young entrepreneurship and inclusive sustainable development;
- Expanding the reach of the AIR Centre scientific agenda through a wider engagement with the academia to demonstrate the societal relevance and public value of research.
Doctoral research work will be carried out entirely or partially in a Portuguese institution.
Scholarships are annual, renewable to a maximum of 4 years.
Applications and all supporting documents must be submitted online using the Application Form available on each scholarship page. Applications submitted by other means will not be accepted.
Please note that you will need the items listed below. To ease the submission process, we suggest you gather them before you start your application:
- Copy of your Identification Document (ID card, passport);
- Recognition of the foreign academic degrees and the conversion of the respective final grade to the Portuguese grading scale, if applicable;
- Your Curriculum Vitae and saved as PDF;
- A Motivation Letter;
- Your PhD work plan, if applicable (please check scholarship link for details before working on this);
- 2 Recommendation letters.
- Ciência ID
Except for official documents, application and all related documents must be submitted in English.
Notification of results
Evaluation results will be communicated to the email address provided by the candidates in the application form.
Before applying, IT IS STRONGLY RECOMMEND that you carefully read the Public Notice of the Call for detailed information on the application, evaluation and selection process. Public Notice can be found on each scholarship page.
To access the Application Form (found within each scholarship page), you need to Register (create an account). When doing so, please make sure to write your email address correctly since all relevant information regarding your application will be sent to that email. Once you register, a password will be sent to your email and you can then Log In. Access the Scholarship Programme tab and scroll down to see all the available scholarships.
You can only submit one application for each scholarship. You can edit and save the application form at any time. The form will be available on the platform for editing until the application deadline, or until you submit the application. Once you submit your application, you will not be able to un-submit or make any changes.
Please note that the application to this scholarship program does not grant you a place in a PhD programme. Make sure you apply to the PhD programme identified in each scholarship.
Questions related to the application process or Application Form should be addressed to the AIR Centre through the email firstname.lastname@example.org using the following subject line: AIR Centre PhD Scholarship Programme – [your name]. The AIR Centre will reply to all information requests up to 3 working days before the applications submission deadline. Before contacting the AIR Centre carefully read all the documents related to the Call and the information available on the AIR Centre’s website.
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