Skip to content

Warehouse Robotics Market Expected to Grow to $31.3 billion with a 16.41% CAGR by 2030

Utilizing technology, software, and control systems to increase production is known as automation in a warehouse. It usually refers to tasks performed in warehouses or distribution centers with little human interaction.

Photo by Petrebels / Unsplash

Table of Contents

Utilizing technology, software, and control systems to increase production is known as automation in a warehouse. It usually refers to tasks performed in warehouses or distribution centers with little human interaction. The global warehouse robotics market size is expected to reach USD 31.3 billion by 2030, growing at a CAGR of 15.51% during the forecast period (2022–2030), according to a research manager with Straits Research P. Ltd.

A rising percentage of SKUs (stock-keeping units) is standard in the industry since new products are frequently released, and to meet the long-tail expectations of their customers, more than 50% of organizations plan to strategically increase the number of inventory SKUs they have available over the projected period. Automated, efficient mini-load storage and retrieval systems (AS/RS) can handle individual totes, cases, trays, and boxes while maximizing storage and freeing up valuable delivery and labor resources to keep up with this expansion.

As warehouses expand to meet the need for home delivery (or curbside delivery), there is potential for several e-commerce segments, with the most recent generation picking robots and AGVs. They seem to be incredibly well-adapted for fulfillment operations involving large numbers of small orders for large SKU ranges scattered over large warehouse zones. Warehouses must scale up and satisfy the requirements for an intelligent, efficient, and automated warehouse due to the advent of always-on e-commerce, the need for speedier responses, and the desire to manage a more significant number of SKUs with fewer errors.

As a result of the development of AMRs for warehouse and material management applications, businesses that provide warehouse robots now have a lucrative opportunity. AMRs are preferable to manual means of material movement like manned forklifts. These robots have safety sensors that prevent collisions from occurring. Their accuracy varies according to how well they function and how their choices affect productivity and security in diverse contexts. The location and surroundings may be calculated more or less accurately in AMRs, depending on the sensors and algorithms used. AMR technology advancements are also creating opportunities for AI integration in warehouse robots.

North America markets are expected to proliferate at a CAGR of 15.92%, accounting for $6 billion by 2030. The growth of e-commerce, technological advancements that have made robots better and smaller, lower prices, and a labor shortage in some industries are the primary forces behind the increased employment of robots in North American warehouses and distribution centers. In contrast, a rise in both high- and low-skill occupations, including management positions on the one end and vocations that assist or look after others on the other, is being observed. Several retailers in North America are collaborating with technology firms to co-develop robots that might be deployed in retail establishments to assist customers in finding the items they are looking for.

Key Highlights from the study include:

  • The Storage section is projected to advance at a CAGR of 15.27% and hold the largest market share over the forecast period.
  • Based on type, the global warehouse robotics market is segmented into Industrial Robots, Sortation Systems, Conveyors, Palletizers, Automated Storage & Retrieval Systems, and Mobile Robots. The Mobile Robots (AGVs and srs) section is projected to grow at a CAGR of 16.72% and hold the largest market share over the forecast period.
  • Region-wise, the global warehouse robotics market is categorized into North America, Europe, Asia-Pacific, and LAMEA. APAC exceeds the rest of the world.

Latest