Predictive Field Mapping for Harvester Weed Patch Control

Solution Overview

Problem

Agricultural harvesters face performance degradation when encountering weed patches, as weeds can impede machine operation and increase moisture content, leading to inefficiencies and potential damage.

Innovation Solution

The use of in-situ sensors on agricultural work machines to gather data on agricultural characteristics, combined with prior information maps, generates predictive maps that forecast agricultural characteristics such as weed intensity and biomass, enabling automated machine control to navigate weed patches efficiently.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If the harvester operates through fields with weed patches, then the harvesting operation can continue without interruption, but machine performance degrades and operational inefficiencies increase

Engineering Contradiction:

Improveharvesting operation continuityVSAvoidmachine performance

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary actions by generating predictive maps that forecast weed patch locations before the harvester reaches them. In-situ sensors detect agricultural characteristics ahead of time, and the predictive map generator creates advance warnings of upcoming weed patches, allowing the operator to prepare control modifications before encountering the problematic areas.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If the operator manually modifies control upon encountering weed patches, then machine performance can be adjusted to handle weeds, but response time is delayed until the weed patch is encountered

Engineering Contradiction:

Improvemachine performance adaptationVSAvoidresponse time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by generating predictive maps that forecast weed patch locations before the harvester reaches them. In-situ sensors detect agricultural characteristics ahead of time, and the predictive map generator creates advance warnings of upcoming weed patches, allowing the operator to prepare control modifications before encountering the problematic areas.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback by using in-situ sensors to continuously detect agricultural characteristics and feed this information back to the predictive map generator. This closed-loop feedback mechanism allows the system to update predictions and adjust control recommendations in real-time based on actual field conditions encountered during harvesting.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250151648A1Machine control using a predictive map

Publication Date: 2025.05.15 DEERE & CO

AI summary

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.