Warehouses are a crucial link in supply chains, as they handle storage and inventory management and thus connect demand with supply. Their importance is also becoming increasingly clear in light of recent developments, such as more same-day deliveries within e-commerce and supply chain disruptions. Previous research further reveals that order picking can be considered the most labour-intensive and most expensive activity in a warehouse setting. In fact, in most warehouses, order picking is still done manually, as people can handle unexpected changes more flexibly compared to machines. In addition, order picking is perceived as a time-consuming task. Several improvements can thus still be realised. One possible optimisation consists of implementing AMRs that can assist an order picker with the task. The robot would then not replace the human but rather complement it. In this way, among other things, non-value-added travelling time can be taken over by the robot, and the order picker can consequently deal with a new order. The aim of this project is to assess the cooperation between humans and robots in order picking based on real-life applications, providing a better understanding of the potential benefits in terms of both operational performance, as well as well-being.