Abstract: Although autonomous robots have great potential to boost efficiency and throughput across the whole retail chain, they are mostly being deployed in large warehouses and distribution centers. Deploying robots in stores with customers, such as supermarkets, requires substantially more development efforts since they need to safely operate around customers and reliably cope with various uncertainties and disturbances, such as misplaced products. We present our recent efforts in developing a mobile manipulator platform for order picking in realistic supermarket settings. Our robot platform uses state-of-the-art perception and planning algorithms to robustly pick items in the presence of disturbances. In particular, it successfully demonstrates adaptive decision making and rapid replanning. Our robot allows adding new products and teaching new picking maneuvers from demonstrations. We validated our robot in a recreated supermarket in our lab and in a test supermarket of a large Dutch retailer. Our results show how our robot successfully recovers from various disturbances, including misplaced products, errors in picking, and from human interaction. We summarize our lessons learned to bring autonomous robots into real retail environments with customers.
