Mobile Grow Tray Robots for High-Density Vertical Farming
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Solution Overview
Problem
Current hydroponic grow space systems face challenges such as high manual labor costs, inefficiencies, and limited flexibility in maintaining and accessing plants, which hinder labor cost reduction and productivity.
Innovation Solution
A grow space automation system featuring mobile robots with sensors, mobility mechanisms, processors, and lifts that allow for unobstructed navigation and task performance within densely packed grow trays, including designs for angled supports and multi-robot coordination to maintain high plant site densities and enable efficient transport and task automation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional farming methods are used with vast amounts of space, then crops can be grown, but space requirements are excessive and weather dependency increases
Solution Approach 1:
The patent implements multi-level stacked grow trays arranged vertically to maximize space utilization. Instead of expanding horizontally, the system stacks trays in multiple levels, allowing crops to be grown in three-dimensional space. This vertical arrangement dramatically increases planting density while reducing the horizontal footprint of the grow space.
Solution Approach 2:
The grow space is divided into modular stacked trays that can be independently configured and manipulated. Each tray represents a discrete unit that can be individually accessed, moved, or adjusted by mobile robots. This segmentation enables efficient space utilization while allowing targeted access to specific crop areas without disturbing the entire grow space.
2Reliability
If ground farming is used to shield crops from outside elements, then crops are protected, but vast space is still required and farmers must traverse the space to provide care
Solution Approach 1:
The system employs mobile robots that can dynamically move between and among stacked trays to perform maintenance tasks. Rather than fixed infrastructure requiring human traversal, the mobile robots adapt their positions and paths based on which trays need attention, making the system flexible and efficient in accessing crops for watering, monitoring, and other care activities.
Solution Approach 2:
Mobile robots autonomously navigate the stacked tray structure and perform maintenance tasks on crops without human intervention. The robots independently identify which trays require attention, move to appropriate positions, and execute care activities such as monitoring plant health, managing irrigation, and detecting pests, thereby eliminating the need for farmers to physically traverse the grow space.
3Productivity
If manual labor is used for crop maintenance, then crops receive care, but labor costs are high and efficiency is limited
Solution Approach 1:
The patent replaces manual mechanical labor with automated mobile robots equipped with sensors, processors, and actuators. These robots use computer vision, LIDAR, and other sensing technologies to detect crop conditions, navigate the stacked tray structure, and perform maintenance tasks. This substitution of mechanical human labor with automated robotic systems dramatically increases productivity while reducing labor costs and enabling higher automation levels.
Solution Approach 2:
The mobile robots are equipped with sensors and processors that continuously monitor crop conditions, tray positions, and environmental parameters. This feedback information is used to autonomously adjust robot behavior, optimize maintenance schedules, and adapt to changing grow space conditions. The feedback loops enable the automated system to respond dynamically to crop needs, improving overall maintenance efficiency and productivity.
4Extent of automation
If traditional manufacturing equipment is purchased to reduce labor costs, then labor costs decrease, but equipment cost increases significantly
Solution Approach 1:
The mobile robots are designed as multi-functional platforms that can perform various maintenance tasks across different tray configurations and crop types. Rather than requiring separate specialized equipment for each function, a single robotic platform can adapt to multiple tasks through software control and interchangeable end-effectors. This universality reduces overall equipment costs while achieving high automation levels for labor cost reduction.
Solution Approach 2:
The robotic system is designed to be dynamically adaptable to different grow space configurations, tray arrangements, and crop requirements. Rather than fixed, expensive specialized equipment, the mobile robots can reconfigure their paths, adjust their operations, and adapt to changing conditions through software control. This dynamic flexibility reduces equipment costs while maintaining high automation capabilities for reducing labor expenses.
Data Source
AI summary
A grow space automation system. The system includes growing plants in grow modules that are individually moveable. One or more mobile robots can navigate around a grow space, bring any grow module from one location to another, and perform grow space operations. The grow space operations can be automated using robot-based actuation of automation fixtures. Interactions with plants can also be achieved via robot attachments. The grow space is configured to allow maximum grow tray density while still maintaining traveling pathways for the mobile robots. Multiple mobile robots move about the grow space in their respective travel zones in coordination with one another via navigation planners. Multi-robot coordination can also be achieved using a central server. Local leveling of grow trays can be achieved via laser levels.