Robotic Item Picking with Bulk Transfer and Single-Item Selection
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Solution Overview
Problem
Existing technologies face challenges in efficiently automating the picking process of items from both homogenous and heterogeneous storage containers, which is labor-intensive and costly.
Innovation Solution
The development of autonomous robotic systems that include a surface, a first item manipulation apparatus with a first end effector, and a second item manipulation apparatus with a second end effector. The first end effector is configured to releasably couple with multiple items and transfer them onto a surface, while the second end effector engages and transfers a single item into a second receptacle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual item picking is used, then flexibility and adaptability are maintained, but labor costs are high and productivity is low
Solution Approach 1:
The system divides the picking process into two distinct phases: a bulk transfer phase using a first end effector to move multiple items at once, and a selective picking phase using a second end effector to pick individual items. This segmentation allows the system to achieve high productivity through automated bulk handling while maintaining the flexibility of selective picking, thereby resolving the contradiction between productivity and system complexity.
Solution Approach 2:
The surface acts as an intermediary between the storage container and the picking location. Items are first transferred to this intermediate surface, then selectively picked from there. This intermediary surface simplifies the picking operation by providing a stable, organized platform from which items can be easily grasped and transferred, reducing the complexity of direct picking from cluttered containers.
2Productivity
If automated picking systems are implemented, then productivity increases, but system complexity and cost increase
Solution Approach 1:
The automation is segmented into two levels: high-level automation for bulk item transfer using the first end effector, and selective automation for individual item picking using the second end effector. This graduated approach to automation achieves high productivity through automated bulk handling while keeping the automation level manageable by separating complex bulk transfer operations from simpler selective picking operations.
Solution Approach 2:
The system uses universal end effectors that can handle multiple types of items through standardized gripping mechanisms. The first end effector is designed to accommodate various item sizes and shapes for bulk transfer, while the second end effector provides adaptable grasping for selective picking. This multi-functionality reduces system complexity by avoiding the need for specialized equipment for each item type.
3Quantity of substance
If items are stored in heterogeneous containers, then storage efficiency improves, but picking accuracy and speed decrease
Solution Approach 1:
The system performs preliminary organization by transferring items to a structured surface grid before the picking operation begins. This preliminary action creates a predictable, organized arrangement of heterogeneous items, making them easier to identify and locate. The surface provides reference points and spacing that enhance vision system accuracy, thereby improving item identification precision without sacrificing storage efficiency.
Solution Approach 2:
The system replaces manual visual search and identification with automated vision systems and computational algorithms. The vision system captures images of the organized items on the surface, and software algorithms automatically identify item locations, types, and quantities. This substitution of mechanical/visual processes with automated sensing and computation dramatically improves identification accuracy for heterogeneous items while maintaining high picking speeds.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution significantly reduces labor costs, accelerates order fulfillment processes, and improves order fulfillment quality by reducing human errors, thereby enhancing inventory accuracy and overall efficiency.
Implementation Method 1
The first end effector can be configured to releasably couple with multiple items in a first item receptacle
Implementation Method 2
a mechanism configured to vibrate the surface to cause separation of the multiple items on the surface
Implementation Method 3
The second end effector can be configured to engage with a single item of the multiple items on the surface
Data Source
AI summary
This document describes systems and methods for enhancing the efficiencies of order fulfillment and inventory management processes. For example, this document describes automated robotic systems that can autonomously pick and place a particular quantity of desired items from a container that is storing the items. The autonomous robotic systems can thereby facilitate order fulfillment and inventory management processes in an efficient manner. In particular, the systems and methods described herein can greatly reduce the amount of time required for a human worker to pick orders. Accordingly, the efficiency of item picking processes, as measured by the number of line items picked per human labor hour for example, is greatly enhanced.