The SEACLEAR kick-off meeting took place on the premises of the project leader, TU Delft. During this meeting, we refined the objectives and tasks of the project with all the partners.

As with any complex system, we must define the use cases before developing any of the technology involved. For the duration of this project, we will focus on two use cases, one being the tourism sector and the other port management.

At the core of our system are the robots that will do the actual work. SEACLEAR required the development of a new autonomous surface vehicle (SeaCAT), and a new underwater observation robot (MiniTortuga). Furthermore, a reliable way of deploying and retrieving all the robots is necessary.

Sensing is the way our robots locate themselves and find litter. In SEACLEAR, we are mainly relying on cameras and sonars to search for litter, and we have to integrate these sensors with the rest of the equipment.

A key component for the collection of litter is the system's gripper, which needs to be mounted under the collection ROV. The gripper should be suitable for collecting a wide range of litter found on the ocean floor, while ensuring that no marine life forms are harmed.

The collection basket is the place where the litter will be stored until it is safely transported to the shore. It must be compatible with the gripping system and must ensure that no litter escapes once collected.

Due to signal loss underwater, the ROVs cannot rely on satellite positioning systems for their localisation. Therefore, we need to develop solutions for fusing different sensor data to estimate the position of the robots underwater. Furthermore, we develop advanced techniques for controlling the trajectories of the robots efficiently while in water.

To collect litter, it must first be detected. To do this, we rely on machine learning techniques with deep neural networks. A key objective of these algorithms is to correctly distinguish between marine litter and marine life forms, so that we only collect what we intend to.

To coordinate the operation of the robots, we need sufficiently accurate knowledge of the ocean floor bathymetry. Identified litter must moreover be placed on this map, so that the robots know where to go to collect it. Our goal is to build this combined map of the ocean floor in an energy and time efficient way.

Besides the trajectory control needed for the robots, the SEACLEAR system must define higher level tasks for them. This includes the paths they will follow to detect the litter more efficiently, but also the order that the detected litter will be collected afterwards.

SEACLEAR is aiming to combine several individual components together, with a considerable amount of data that need to be shared between each component of the system. Therefore, we aim to develop reliable and efficient communication systems so that the computational intensive tasks can take place where it is more suitable.

The end goal of this project is to demonstrate its capabilities on different sites, with different needs. For SEACLEAR we have identified two locations for performing these demonstrations: The Dubrovnik area (tourist use case), and the Hamburg Port (port use case).

Our goal is to make the SEACLEAR system commercially viable. We aim at exploiting the results of this project both by selling the system and by providing it as a service to local authorities, ports, or other stakeholders.