Planter Lookahead Control for Accurate Curved-Path Row Switching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing agricultural path prediction systems lack robust navigation information, leading to inaccuracies in non-linear movements and premature activation/deactivation of row units, resulting in inefficiencies and financial losses due to over or underplanting.
Innovation Solution
A predictive path lookahead system that utilizes GPS coordinates, speed, attitude, tilt, acceleration, and other navigation factors, combined with a motion model and sensors, to generate a predicted trajectory and automatically control row units, enabling accurate and efficient operation even in curved paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing path prediction systems use only current speed and geometry, then the system complexity is low, but the trajectory prediction accuracy deteriorates in non-linear movements
Solution Approach 1:
The system performs preliminary actions by collecting and processing robust navigation information (GPS coordinates, speed, attitude, tilt, acceleration) before the agricultural equipment actually executes the maneuver. This advance preparation allows the motion model to predict curved trajectories accurately, enabling the system to anticipate future positions rather than merely reacting to current state, thus resolving the contradiction between accuracy and complexity.
Solution Approach 2:
The patent introduces a motion model as an intermediary component that processes navigation information and generates predicted trajectories. This intermediary layer transforms raw sensor data into meaningful trajectory predictions, allowing the system to achieve high accuracy in non-linear movements without requiring direct complex control mechanisms, thus bridging the gap between simple inputs and accurate outputs.
2Measurement precision
If existing systems rely on current geometry only, then the response time is fast, but the path planning accuracy deteriorates in curved paths
Solution Approach 1:
The system performs preliminary computations by continuously processing navigation information through the motion model to generate predicted trajectories in advance. This allows the path planning to be based on pre-computed accurate trajectory data rather than requiring complex real-time calculations during execution, thus maintaining both high accuracy and acceptable response time.
3Manufacturing precision
If row units are controlled based on current position only, then the control simplicity is high, but the planting accuracy deteriorates due to premature ON/OFF activation
Solution Approach 1:
The control system performs preliminary actions by using the predicted trajectory to determine when row units should be turned ON or OFF. Instead of reacting to current position alone, the system anticipates future positions along the curved path and pre-positions the row units accordingly, preventing premature activation or deactivation and ensuring accurate planting even during turns.
Solution Approach 2:
The system implements feedback by continuously monitoring the actual position of the agricultural equipment and comparing it with the predicted trajectory. This closed-loop control allows the system to adjust row unit activation timing based on the difference between predicted and actual positions, maintaining planting accuracy while adapting to real-world variations in equipment movement.
Data Source
AI summary
A predictive path lookahead system is used with an agricultural vehicle and/or agricultural implement. A variety of factors relating to the vehicle and/or implement are input into the system in order to measure and process the vehicle and/or implement's motion. A navigation orientation tool is also input into the system. The system then generates a predicted lookahead trajectory and/or predicted future position of the vehicle and/or implement and can display the predicted lookahead trajectory and/or predicted future position to a user. The system can automatically turn ON and/or turn OFF a row unit or can manually alert a user when to do so based on the predicted trajectory of the implement. The system can engage in auto-steering to operate the vehicle and/or implement autonomously.