Rail-Mounted Pneumatic Picking Robot for Dense Storage Grids
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Solution Overview
Problem
Existing storage systems face inefficiencies in storage density, order fulfillment times, and throughput due to the need for extensive container transportation and the inability of robots to consistently grasp a wide variety of products, particularly those with varying sizes, shapes, and materials.
Innovation Solution
A storage system with a mobile, manipulator robot equipped with a pneumatic gripping tool and a fluid supply line, allowing the robot to traverse parallel rails and efficiently pick items using a pneumatic gripping tool, coupled with a central processor for autonomous or tele-operated control, enabling the robot to adapt to different product types and sizes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If containers are stacked in adjacent rows without aisles to increase storage density, then storage density is improved, but container retrieval time increases due to longer transportation distances
Solution Approach 1:
The patent introduces a robotic vehicle as an intermediary agent to retrieve containers from densely stacked storage locations and transport them to picking stations. The robot navigates through the stacked container arrangement, lifting and transporting containers without requiring human operators to physically access dense storage areas, thus resolving the contradiction between high storage density and retrieval efficiency
Solution Approach 2:
The patent replaces manual container handling with an automated robotic system equipped with lifting mechanisms. The robotic vehicle autonomously navigates, lifts, and transports containers, substituting human mechanical operations with automated mechanical systems, thereby maintaining fast retrieval times even in densely stacked configurations
2Productivity
If multiple vehicles are added to the grid to increase throughput, then order fulfillment speed is improved, but grid congestion increases causing system gridlock
Solution Approach 1:
The patent implements dynamic routing and coordination algorithms that allow multiple robotic vehicles to adapt their paths and operations in real-time based on current grid conditions. The system dynamically adjusts vehicle routes, task assignments, and navigation to prevent congestion and gridlock, enabling high throughput with a manageable number of vehicles
Solution Approach 2:
The patent incorporates feedback mechanisms where the central controller continuously monitors vehicle positions, grid congestion levels, and order priorities. Based on this feedback, the system optimizes task allocation and routing decisions, allowing the fleet to self-regulate and maintain efficient operation without excessive vehicle deployment
3Adaptability or versatility
If a pneumatic gripping tool is used to grasp various products, then adaptability to different product types is improved, but device complexity increases due to fluid supply requirements
Solution Approach 1:
The patent merges the fluid supply system with the robotic vehicle's existing infrastructure by integrating pneumatic lines into the vehicle's frame and control systems. The pneumatic gripping tool shares the vehicle's power and control architecture with other subsystems, consolidating complexity rather than adding to it, while maintaining versatile product grasping capability
4Loss of energy
If containers are transported to picking/sorting zones only after multiple orders are received, then transportation efficiency is improved, but order fulfillment time increases for infrequently ordered products
Solution Approach 1:
The patent implements dynamic batch consolidation algorithms that adaptively determine when to transport containers based on real-time order patterns, product demand frequency, and vehicle availability. For frequently ordered products, the system waits to consolidate multiple orders before transportation. For infrequently ordered products, the system adjusts to trigger earlier transportation, thereby optimizing the balance between transportation efficiency and fulfillment time based on actual demand dynamics
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
The system enhances storage density and order fulfillment efficiency by allowing the robot to grasp a wide range of products without the need for bulky air compressors, reducing downtime, and increasing throughput by enabling quick switching between gripping tools and requesting assistance when needed.
Implementation Method 1
a pneumatic gripping tool configured to pick inventory items
Data Source
AI summary
A storage system configured to house a plurality of containers housing inventory items includes support members, a first set of parallel rails to support a mobile, manipulator robot, and a fluid supply line having a plurality of valves disposed within the fluid supply line. Each of the valves having a closed condition in which the supply line is in fluid isolation from an outside environment and an open condition in which the supply line is in fluid communication with the environment such that the supply line is configured to supply fluid to a mobile, manipulator robot. Mobile, manipulator robots for retrieving inventory items stored within the containers and retrieval methods are also disclosed herein.