Robotic Order Picking With Rebin Aggregation for Early Pickup
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Solution Overview
Problem
The process of picking and packaging items in retail stores is labor-intensive and inefficient, particularly when customers need to pick up orders early or restock shelves.
Innovation Solution
A system utilizing robots to pick and rebin items, where picking robots move items to a rebin robot for aggregation and packaging, reducing the need for robots to travel between multiple locations and allowing for efficient early order pickup and restocking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual picking and packaging processes are used, then flexibility in handling early order pickups is maintained, but labor intensity and inefficiency increase
Solution Approach 1:
The robotic system performs picking and packaging operations autonomously without human intervention. Robots navigate store aisles, locate items using vision systems, pick products, and deliver them to designated locations or customer pickup points, enabling the system to serve itself and eliminating manual labor while maintaining operational flexibility.
Solution Approach 2:
Manual mechanical operations by human workers are replaced with automated robotic systems equipped with sensors, actuators, and control algorithms. The robotic pickers use computer vision and machine learning to identify and grasp items, replacing human hands and eyes, while automated navigation systems replace human decision-making for route planning.
2Productivity
If robots are deployed for picking and packaging, then picking efficiency is improved, but the complexity of coordinating multiple robots and managing item aggregation increases
Solution Approach 1:
The order fulfillment process is divided into distinct segments: item picking by individual robots, item aggregation at designated locations, and final packaging. Multiple robots can work in parallel on different items or orders, and the system coordinates their movements and deliveries without requiring complex inter-robot communication, simplifying the overall coordination challenge.
Solution Approach 2:
A centralized control system or warehouse management software acts as an intermediary between multiple robots and the order fulfillment process. This mediator receives order requests, assigns tasks to appropriate robots, tracks their locations and progress, and coordinates item aggregation at designated locations, thereby simplifying robot-to-robot coordination through a centralizing interface.
3Loss of time
If items are held in robots for scheduled pickup, then customer service flexibility is reduced, but robot travel time and energy consumption decrease
Solution Approach 1:
Items are picked and held in designated locations or intermediate storage areas in advance of the scheduled pickup time. Robots complete picking operations ahead of time and deliver items to holding zones where they remain ready for customer retrieval. This preliminary action allows robots to minimize travel time while the system maintains flexibility to accommodate early or delayed pickups by simply adjusting when items are made available for customer collection.
Data Source
AI summary
A computer-implemented method includes receiving an indication that an order scheduled for later pickup is to be picked up earlier than scheduled. A plurality of robots that are holding items that form at least part of the order are then identified and instructed to move immediately to a pickup location and to make the items of the order held by the plurality of robots available for retrieval from the plurality of robots.