RubikCell: Toward Robotic Cellular Warehousing Systems for E-Commerce Logistics
提出一种新型机器人仓储系统RubikCell，结合自动分拣、机器人到货拣选和边拣边分操作，通过单元仓储概念减少机器人移动距离，用数学模型解决单元形成问题，实验验证了有效性。
As e-commerce has become more prevalent, the required logistics operations are challenged by the greater demand for and higher complexity of order picking in warehouses. While goods-to-person (G2P) picking systems, such as robotic mobile fulfillment systems, are becoming popular, there are still challenges in G2P systems, including the unstable performance of human picking due to fatigue and human errors, and the constrained mobility of robots. To tackle these challenges, this article presents a new robotic storage and order picking system, which we call RubikCell. It leverages the strengths of existing warehouse systems and incorporates automatic dispensing, robot-to-goods picking, and pick-while-sort operations. In RubikCell, robots are equipped with trays to store and transport items for an order, instead of moving with heavy pods to workstations as in G2P systems. In addition, the concept of cellular warehousing (CW)—inspired by cellular manufacturing—aims to operate a large warehouse with smaller warehousing cells. This approach reduces the substantial traveling distances of robots, as they move within their dedicated warehousing cells rather than the entire warehouse. A mathematical programming model is developed to address the cell formation problem in CW. Lastly, the implementation of CW principles in RubikCell, forming Robotic CW Systems, renders e-commerce warehousing more flexible, scalable, and reconfigurable. Numerical experiments conducted on this innovative system have confirmed the effectiveness of the cell formation method.