Robot Item Storage Array for Adaptive Warehouse Order Picking
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Solution Overview
Problem
Current robot-assisted order-fulfillment systems are inefficient due to static container structures that do not maximize robot pick efficiency, leading to wasted space and time, as orders are assigned to robots regardless of their location and container size, resulting in suboptimal transportation capabilities.
Innovation Solution
A method and system where a robot navigates a warehouse using barcodes on interconnected item storage arrays to efficiently assign and execute orders based on the array's characteristics, such as the number and dimensions of containers, optimizing order distribution and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static container structure is used on the robot, then the system is simple to operate, but the robot pick efficiency is not maximized and space is wasted
Solution Approach 1:
The container structure is changed from static to dynamic through the use of removable and interchangeable containers. The system allows containers to be attached and detached from the robot base according to order requirements, enabling the robot to adapt its carrying capacity and configuration dynamically. This resolves the contradiction by maintaining operational simplicity through standardized interfaces while maximizing pick efficiency through flexible container selection and arrangement.
Solution Approach 2:
The container system is segmented into multiple independent, standardized containers that can be individually selected and combined. Each container is a discrete unit with standardized dimensions and attachment mechanisms, allowing the robot to carry only the necessary number and type of containers for each specific order. This segmentation enables efficient space utilization and adaptability without complicating the overall system operation.
2Ease of operation
If orders are assigned to robots regardless of their location and container size, then order assignment is simple, but transportation capability is not optimized
Solution Approach 1:
The system incorporates feedback mechanisms where the robot's current location, container configuration, and order requirements are continuously monitored and communicated to the assignment system. This feedback enables intelligent matching of orders to robots based on real-time conditions, optimizing transportation capability while maintaining automated assignment processes. The system uses this information to make adaptive decisions about which robot should receive which order.
Solution Approach 2:
The system performs preliminary actions by pre-configuring containers on robots before orders are assigned. Containers are prepared and positioned on robot bases in advance, and the assignment system takes into account the current container configuration when distributing orders. This preliminary preparation enables more efficient order fulfillment by reducing the need for mid-task reconfigurations and optimizing the matching between robot capabilities and order requirements.
3Adaptability or versatility
If human operators manually traverse the warehouse to pick items, then flexibility in handling complex orders is maintained, but time consumption increases and efficiency decreases
Solution Approach 1:
The robot system is equipped with autonomous navigation and container management capabilities, enabling it to independently traverse the warehouse, locate items, and handle containers without continuous human intervention. The robot can autonomously navigate to storage locations, retrieve items, and return to the fulfillment area, significantly reducing time consumption while maintaining the flexibility needed for complex orders through programmable task sequences.
Solution Approach 2:
The system introduces an intermediary control system that coordinates between human operators and robots. This intermediary manages task allocation, monitors robot operations, and handles complex decision-making, allowing human operators to focus on high-level planning while robots execute time-consuming traversal and picking tasks. This division of labor maintains handling flexibility while dramatically reducing overall time consumption.
Data Source
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AI summary
A method for executing orders by at least one robot on a plurality of items stored at locations throughout a warehouse including reading a bar code affixed to an item storage array disposed on said at least one robot. The item storage array includes a plurality of interconnected containers each for storing items associated with an order. The method also includes using the read bar code to retrieve information about at least one characteristic of the item storage array and assigning an order associated to each of the plurality of containers of the item storage array. The orders are based in part on the at least one characteristic of the item storage array. The method further includes navigating the at least one robot to locations throughout the warehouse to execute the orders associated with each of the plurality of containers of the item storage array.