Recyclable materials recovery is a key element of the circular economy and the EU Green Deal. It is typically performed manually at
large scale Material Recovery Facilities (MRFs) installed close to dense urban areas. Recent advances in AI and robotics have enabled
the automation of several MRF activities. However, they target large waste volumes and are not cost-effective for smaller, less accessible
areas. To accommodate the latter, portable material recovery units can be deployed nearby. Despite the increasing demand for portable
units, offerings lack intelligent, automated components that could significantly increase their productivity. To fill this gap, RECLAIM
will develop a portable, robotic MRF (prMRF) tailored to small-scale material recovery. The proposal exploits well-tested technology
in robotics, AI and data analytics which is improved to facilitate distributed material recovery. RECLAIM adopts a modular multirobot/
multi-gripper approach for material recovery, based on low cost Robotic Recycling Workers (RoReWos). An AI module combines
imaging in the visual and infrared domain to identify, localize and categorize recyclables. The output of this module is used by a multi-
RoReWo team that implements efficient and accurate material sorting. Further, a citizen science approach will increase social sensitivity
to the Green Deal. This is accomplished via a novel Recycling Data-Game that enables and encourages citizens to participate in project
RTD activities by providing annotations to be used in deep learning for the re-training of the AI module. RECLAIM developments will
be implemented and repeatedly assessed in demanding, real material recovery tasks. Three different scenarios will attest its effectiveness
and applicability in a broad range of locations that face material recovery challenges. This will pave the way for the prMRF market
uptake and provide a major boost in making Europe zero polluting, climate-neutral, sustainable and globally competitive.