AGV Cart Shelf Elevation for Faster Retail Item Distribution
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Solution Overview
Problem
In large retail settings, the manual and labor-intensive process of delivering, unloading, and sorting items is inefficient, prone to errors, and wastes time due to the need for manual navigation and incorrect placement of items on carts, leading to delays and inefficiencies.
Innovation Solution
An autonomous ground vehicle (AGV) system with a shelf elevator and drive unit that can adjust shelf heights, autonomously navigate between docking and destination locations, and bid on delivery tasks, using AI to optimize item routing and resource usage, integrating with a conveyor assembly and item identifier to streamline the sorting and transport process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used for item delivery and sorting, then labor flexibility is maintained, but productivity and operational efficiency deteriorate due to labor-intensive operations and delays
Solution Approach 1:
The AGV system performs delivery and sorting operations autonomously without human intervention. The vehicle navigates independently, receives items from conveyor systems, and delivers them to designated locations, enabling the system to serve itself and eliminating the need for manual labor in these operations
Solution Approach 2:
The patent replaces manual mechanical operations with an automated robotic system. The AGV uses sensors, processors, and automated control systems to perform navigation, item handling, and delivery tasks that were previously performed manually by employees
2Loss of time
If employees manually navigate and sort items, then adaptability to changing conditions is maintained, but loss of time increases due to mistakes in shelf location and inefficient routing
Solution Approach 1:
The AGV system incorporates sensors and communication systems that provide continuous feedback to the central processor. This enables real-time monitoring of the vehicle's position, status, and environment, allowing the system to make accurate routing decisions and adjust to changing conditions without manual intervention
Solution Approach 2:
The system pre-plans delivery routes and shelf locations using its database and processing capabilities. By calculating optimal paths in advance and preparing navigation instructions before the AGV begins its journey, the system eliminates delays caused by on-the-spot decision-making and mistakes
3Productivity
If carts are loaded with multiple items for disparate locations, then productivity increases by reducing trips, but loss of time increases due to inefficient unloading sequences
Solution Approach 1:
The AGV system dynamically optimizes loading sequences and delivery routes based on real-time information. The processor calculates the most efficient order to deliver multiple items to different locations, adjusting the plan as the vehicle progresses through its route to minimize total unloading time while maximizing the number of items delivered per trip
Data Source
AI summary
A disclosed system for transporting items to destination locations, for example when receiving inventory at large retail locations, includes an autonomous ground vehicle (AGV) having at least one shelf; a shelf elevator operable to raise and lower the at least one shelf; a drive unit operable to move the AGV between a docking location and a destination location; the AGV able to position the at least one shelf at a different heights for loading and offloading items first height and a second height different from the first height, autonomously navigate between the docking location and the first destination location, and bid on delivery tasks. Some examples are further able to use a cartridge unit to expand cargo capacity. An AGV could analyze the currently-loaded weight and the remaining available space, and dynamically adjust the heights of the shelves according to the dimensions of the assigned items.