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SEarch, identificAtion and Collection of marine Litter with Autonomous Robots

Periodic Reporting for period 1 - SeaClear (SEarch, identificAtion and Collection of marine Litter with Autonomous Robots)

Reporting period: 2020-01-01 to 2021-06-30

Today's oceans contain 26-66 million tons of waste, with approximately 94% located on the seafloor. So far, collection efforts have focused mostly on surface waste, with only a few local efforts to gather underwater waste, always using human divers. No solution exists that exploits autonomous robots for underwater litter collection; the SeaClear project will develop the first. We will create a mixed team of Unmanned Underwater, Surface, and Aerial Vehicles – UUVs, USVs, UAVs – to find and collect litter from the seabed and from the water column, focusing on coastal areas since that is where waste inflow concentrates. The UAVs and an inspection UUV map the litter, aiming to establish correlations between surface and underwater litter. A collection UUV then gathers litter, using a combined suction-gripper manipulator. The end goal is to operate the robots autonomously, without remote human intervention. When fully operational, the SeaClear system aims to detect and classify underwater litter with 80% success rate, and collect it with a 90% success rate; all this at 70% reduced cost compared to human divers.

The SeaClear system will be displayed at four demo sites where an autonomous robot system will be verified: one system for the purpose of cleaning ports in the Hamburg port area on two demo site locations with the end-user Hamburg Port Authority (Germany), another in the area of Dubrovnik, namely near Lokrum Island and one in the area of the Mali Ston Bay, with Regional agency DUNEA (Croatia) as end-user for these areas. With these four demo sites, SeaClear has an overview in completely different sectors, given the fact that we have a pilot site of port location emphasizing maritime industries and two other locations representing protected nature areas, one from the tourism sector and the other from the mariculture sector, namely the shellfish industry. Including all of the mentioned areas, the SeaClear system will face different waste fractions, both from inland and sea origin, and obstacles that need to be solved in order for such a system to be fully functional.
A detailed study of the two areas concerned by the demonstrator case studies (Hamburg port and Dubrovnik) has been performed, including characterizations of litter and several potential sites for each study. The robot hardware in the system (USV, inspection UUV, collection UUV, gripper, collection basket, and interfaces) is at a highly advanced stage of development. Many components are fully ready: USV, collection UUV, the UAV itself; the fully novel gripper and an advanced prototype of the basket are ready for testing. Several components like the inspection UUV and the UAV-USV interface are undergoing production or final tweaks, but their design is finalized.

Major strides have been made on the software side as well. The pipeline has been defined, and work is ongoing on all key components: litter detection, mapping, and cooperative control of the robots. Significant results here include a digital twin (simulator) that includes all the robots in the Hamburg scenario; a mixed model-based and learning-based control strategy for grasping objects with the collection ROV; and a deep reinforcement learning mapping proof-of-concept; the latter two having been validated in simulation.

Regarding system integration, the project concept was analysed together the main system components that were defined. The goal is to provide a robotic solution that can be commanded from shore by operative personnel, but also monitored remotely by clients over internet. Moreover, the appropriate server backbone has been designed and implemented, onto which the envisioned services will be provided. The overall system aims for delivering the navigation and sensor data at hand to the operative personnel with minimal latency, but involves several other actors in the process. The goal is to form the basis for the business logic for the envisioned service. The interfaces of the robotic systems and the selected sensors were studies in order to find appropriate technologies and tools for visualising and distributing the online, or live, data.
The key innovation in SeaClear is that our project is the first to develop an autonomous, robotic solution for cleaning litter off the sea floor. This involves significant advances beyond the state of the art in litter classification, machine learning for mapping, and cooperative and shared control.

We are already making a significant impact with the public, with two popularization videos, two highly successful press releases, and many outreach talks, among others. Stakeholders have started being involved in a community-of-practice in Dubrovnik. We have established connec-tions with several existing companies and projects on related topics. In addition, we have worked out a business plan and a data management plan.

We are currently in the phase of planning our first component tests, bound to happen in September 2021. The information gathered during these tests will help in lowering the barriers in the deployment of robotics-based underwater solutions. The fact that the end-users are involved in this process increases further the chances of successful deployment of the system after the end of the project.
Visualization of SeaClear system