Field Map Guidance Lines for Implement Drift and Width Changes
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Solution Overview
Problem
Conventional agricultural vehicle systems face challenges in accurately navigating and performing operations on fields due to errors in crop row location sensing, implement drift, and differences in operational widths, leading to crop damage and inefficiency.
Innovation Solution
The system generates guidance lines based on field maps created from location data and sensor information, allowing vehicles to accurately traverse fields and perform operations while avoiding crop rows, using a combination of GPS, inertial sensors, and implement sensors to adjust for terrain and implement width variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional agricultural vehicle systems use basic navigation methods, then the system complexity is low, but the positioning precision and crop row location accuracy deteriorate
Solution Approach 1:
The patent combines multiple sensing systems (GPS, inertial sensors, implement sensors) and data sources into a unified guidance system. The field map generator integrates location data from GPS, terrain information from inertial sensors, and implement position data to create a comprehensive field map that improves crop row location accuracy beyond what any single system could provide.
Solution Approach 2:
The patent introduces a field map as an intermediary data structure that mediates between raw sensor data and vehicle control commands. The field map stores processed information about crop row locations, terrain features, and implement positions, serving as a intermediate representation that enables precise navigation without requiring direct complex processing of all sensor inputs in real-time.
2Reliability
If the vehicle uses simple guidance lines without field maps, then the operational speed is high, but the crop damage increases due to inaccurate positioning
Solution Approach 1:
The system performs preliminary actions by generating field maps and guidance lines before the vehicle begins field operations. The field map is created in advance using historical location data, terrain information, and implement positions, allowing the vehicle to follow pre-calculated precise paths without real-time calculation delays during actual crop operations.
Solution Approach 2:
The patent implements feedback mechanisms where implement sensors continuously monitor actual implement position and crop row locations, comparing them against the planned guidance lines. This feedback allows the system to detect deviations and adjust the vehicle path in real-time, ensuring reliable crop damage prevention while maintaining operational speed through automated corrections.
3Measurement precision
If the system accounts for implement drift and terrain variations, then the positioning precision improves, but the device complexity increases
Solution Approach 1:
The patent replaces complex mechanical sensing and adjustment systems with electronic and software-based solutions. Instead of using complex mechanical sensors to directly measure implement position relative to crop rows, the system uses GPS, inertial sensors, and computational algorithms to calculate and compensate for implement drift and terrain variations, reducing mechanical complexity while improving precision.
Solution Approach 2:
The system dynamically changes parameters such as guidance line offsets, vehicle speed, and implement positions based on detected terrain variations and implement drift. The field map generator adjusts operational parameters in real-time to compensate for environmental factors, maintaining positioning accuracy without requiring fixed complex mechanical adjustment mechanisms.
4Productivity
If the vehicle traverses the field multiple times for different operations, then the operational completeness improves, but the loss of time increases
Solution Approach 1:
The patent implements a universal field map and guidance system that serves multiple operations (planting, spraying, harvesting, etc.). The same field map generated from location data and terrain information is reused across different operational passes, allowing the vehicle to efficiently plan and execute multiple operations without recreating navigation data each time, thus improving operational completeness while minimizing time loss.
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed for field operations based on historical field operation data. An example apparatus disclosed herein includes a field map generator to generate a field map including locations of a plurality of crop rows, the locations of the plurality of crop rows determined based on a first implement path travelled by a first implement of a first vehicle during a first operation, the first implement having a first operational width, the first implement path different from a first vehicle path of the first vehicle during the first operation, and a guidance line generator to generate a guidance line for a second vehicle during a second operation on the field, the second vehicle including a second implement to perform the second operation, the second implement having a second operational width different from the first operational width, the guidance line based on (a) the field map and (b) the second operational width.