The current boom in e-commerce is challenging the logistics industry because shipment volumes are growing rapidly and online retail typically requires more logistical work per item compared to traditional brick and mortar retail. Manual picking is currently preferred when the number and variety of objects increases because automation becomes increasingly challenging. The specific need addressed in the project is the robot-based automatic collection of sets of small objects in weakly-engineered warehouses. The goal of the project is to address this need by the realisation of the innovation potential of the GOAL-Robots FET project technology applied to industry-relevant warehouse environments. In particular, the project will show that the “open-ended autonomous learning” technology developed within the GOAL-Robots project allows the creation of general-purpose robots for object-retrieval capable of autonomously learning to reach, grasp, and collect a large variety of objects, independently of their shape, rigidity, position, and orientation on shelves. This technological transfer will be achieved through three objectives: (a) the implementation of a demonstrator to show the potential of the technology to the target stakeholders; (b) the technology assessment of the GROW solution involving relevant stakeholders and partners for technology transfer, validating the innovation and its commercial viability; (c) the development of the business case and plan, the dissemination of the solution, and the preparation of communication material to reach potential stakeholders and support the implementation of an effective marketing strategy.