Autonomous Grain Sampling and Grading With LiDAR and NIR
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current grain processing facilities require human operators throughout the grain processing sequence, leading to high operational costs and limited delivery times for farmers, as well as bottlenecks at facilities due to the need for human presence during grain handling.
Innovation Solution
An autonomous grain receiving and loadout facility that autonomously interacts with truck drivers, samples, grades, and handles grain without constant operator coverage, using LiDAR sensors and NIR sensors to determine sampling and grading parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If human operators are used to handle grain sampling and grading, then operational control and decision-making are maintained, but operational costs increase and facility availability is limited
Solution Approach 1:
The autonomous sampling and grading system performs operations independently without requiring human operators. The robot navigates facilities, collects grain samples, and the grading system analyzes samples automatically, making the system self-sufficient in executing its core functions.
Solution Approach 2:
Manual mechanical operations by human operators are replaced with an automated robotic system. The robot uses sensors and automated mechanisms for sampling, while the grading system uses optical and analytical instruments to replace human visual inspection and manual grading processes.
2Productivity
If human operators are required during grain processing, then quality control is maintained, but facility operating hours are limited and farmer delivery flexibility is reduced
Solution Approach 1:
The grading system incorporates feedback mechanisms where sample results are analyzed and used to determine disposition actions. The system continuously monitors grain quality parameters and adjusts processing decisions based on real-time analysis, ensuring consistent quality control throughout extended operating hours.
Solution Approach 2:
The autonomous system enables continuous operation of the grain facility without interruption by human shifts or breaks. The robot and grading system can operate continuously, allowing the facility to process grain around the clock and maintain consistent quality control throughout all operating hours.
3Measurement precision
If traditional sampling methods are used, then equipment simplicity is maintained, but sampling accuracy and representativeness are limited
Solution Approach 1:
The robotic sampling system is designed to handle multiple sampling scenarios and grain types with a single versatile platform. The robot can navigate different facility layouts, access various grain storage locations, and collect samples from different grain conditions, making the sampling system universally applicable across diverse operational contexts.
Solution Approach 2:
The system transitions from traditional single-point sampling to multi-dimensional sampling by collecting samples from various locations, depths, and orientations within grain storage. The robot moves through three-dimensional space to access different grain layers and regions, providing a more comprehensive and representative sample set.
4Productivity
If manual grain handling procedures are used, then operational simplicity is maintained, but bottlenecks occur at facilities and farmer delivery efficiency is reduced
Solution Approach 1:
The grain processing operation is divided into distinct automated segments: robot navigation to sampling locations, sample collection, sample transport to grading system, grain analysis, and disposition decision-making. Each segment operates independently and automatically, eliminating bottlenecks by parallelizing operations and removing sequential human handling steps.
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
Enables continuous grain processing operations, reducing costs and maximizing farmer delivery times by eliminating the need for constant human presence, while improving grading accuracy with additional parameters beyond traditional methods.
Implementation Method 1
The sampling system includes at least a robot with a light detection and ranging (LiDAR) sensor system
Implementation Method 2
controlling, by the one or more processors, a first sensor system to measure first data for the respective sample, wherein the first sensor system comprises a near infrared (NIR) sensor
Data Source
AI summary
Processes for an autonomous grain facility are described herein. The process could include sampling and grading. For sampling, the system controls a robot to capture position data of a trailer and area data of grain, determines one or more sampling areas within the trailer, and controls the robot to obtain a sample from each of the sampling areas. For grading, the system measures data with both a near infrared sensor and a second sensor, analyzes all of the data to determine a dispositive action to be performed on the respective sample, and controls the system to perform the dispositive action.