Cainiao unveils lift-robot system that retrieves goods from four sides, boosting storage density 20%

Cainiao updated its self-developed lift-robot system at CeMAT Asia, roboticsandautomationnews.com reported. The updates include retrieval from four sides, double-deep storage and a next-generation robot scheduling system. According to the report, the updated system increases operational efficiency by 15% and storage density by 20%.

Combining four-sided access with double-deep storage concerns how warehouse space is used while making use of the inner part of shelving. Cainiao's simulation tool was also reported to help evaluate layouts and investment and returns before deployment, making warehouse configuration—not just equipment selection—part of the deployment decision.

The reported update brings together changes to how robots move and retrieve goods and to how warehouse storage is arranged. Combining access to bins from four sides with double-deep storage that reaches the inner part of shelving could change the options for designing aisles and shelf rows. The report says conventional systems typically retrieve goods from two sides, while Cainiao's system can access them from four sides and uses fewer lift lanes to improve space utilization. This suggests that the value of deployment depends not only on the robots' performance but also on the design of the entire warehouse, including shelves, aisles and storage locations. The reported 15% increase in operational efficiency and 20% increase in storage density refer to two different operating metrics. However, the report does not specify the comparison baseline, measurement conditions or size of the warehouse involved. The figures therefore cannot be directly compared as deployment results across different warehouses; the conditions for real-world use need to be confirmed. In particular, the types of SKU mix, inbound and outbound volumes, and warehouse dimensions under which four-sided access and double-deep storage can maintain efficiency are key to determining the system's scope of application. The warehouse-planning simulation tool also has a role distinct from equipment specifications. According to the report, users can create warehouse layouts and visually assess investment and returns before deployment. This appears intended to help users consider operational plans at the layout-planning stage, rather than make adjustments after installing the robots. However, the information provided does not show how closely simulation results correspond to actual operating rates or investment returns. The next points to confirm are the conditions used to calculate the 15% and 20% figures, any inbound and outbound constraints under double-deep storage, and how the scheduling system coordinates multiple robots. The report also does not specify the warehouse conditions that can be configured in the simulation tool or how its results are validated. Clarification on these points would make it possible to assess more concretely whether higher storage density can be achieved while maintaining the required throughput.