Robots are increasingly being deployed in retail environments.1 The reasons for this include: to relieve staff from the performance of repetitive and mundane tasks; to reallocate staff to more valueadded, customer-facing activities; to realize operational improvements; and, to utilize real-time instore generated data. Due to the impact of the 2020 Coronavirus outbreak, we can now add a new reason to use robots in retail: to assist with customer and employee safety.

In this Research Article, we present information on the benefits associated with deploying robots in stores. Estimates of the size of the global retail robot market are advanced. The impact on demand for robots in the grocery industry, in light of the Coronavirus outbreak, is discussed as well. This is followed by a review of U.S. retail robot deployments and the advancing of some emerging applications.

In summary, we find that the trend toward deploying robots in retail environments is accelerating.2 The reasons for this include their functional utility, advances in AI, and the ability to address both labor challenges and customer and employee safety concerns. The introduction of new uses of realtime, in-store generated data is another advantage. Further, the movement toward multimodal robots that are efficient at performing various functions adds to the value equation.3 We also find that changing consumer behavior to increase online purchases, especially in grocery, is a major impetus fueling this movement.

Finally, establishing industry standards, which is ongoing, will fuel adoption. Previous impediments to adoption, which are not detailed here, are also at play. These, for the most part, include issues of cost and training. The costs of robots will decrease, and the ROI will greatly increase, as complex computing moves off the payload via 5G and sensor costs continue to decrease. Increased vendor competition will also be a factor. The cost and complexity associated with environmental training are also being addressed via the introduction of synthetic data.