Off-Road Vehicle Guidance System Adapting to Crop Row Gaps
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Solution Overview
Problem
Existing crop row sensors struggle to provide reliable guidance for off-road vehicles, especially when there are gaps in crop rows or when vehicles travel at higher speeds, as they fail to accurately estimate the central position of the vehicle with respect to the crop row.
Innovation Solution
A system that determines a primary guidance path based on sensed position data from crop row sensors and switches to a secondary guidance path using historic path heading data when gaps are detected, ensuring accurate vehicle alignment and navigation through curvature or linear path estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If crop row sensors are used to sense position data for guiding off-road vehicles, then the vehicle can be guided along crop rows for agricultural tasks, but the guidance becomes unreliable when there are gaps in the crop row or when the vehicle travels at higher speeds
Solution Approach 1:
The system dynamically switches between two guidance modes: primary guidance using real-time crop row sensor data and secondary guidance using historic path information. This dynamic adaptation allows the system to maintain reliability whether the vehicle is traveling at low speeds with continuous crop rows or at high speeds with gaps in the crop rows, directly resolving the contradiction between guidance reliability and adaptability to varying conditions
Solution Approach 2:
The system changes the guidance parameter source based on detected conditions. When gaps in crop rows or high speeds are detected, the system transitions from using real-time sensor parameters to using historic path parameters, allowing reliable guidance across varying operational conditions without requiring a complete system redesign
2Measurement precision
If crop row sensors contact the plants to establish central position, then the vehicle alignment with crop row is improved, but the system fails when plants are missing or damaged
Solution Approach 1:
The system introduces an intermediary decision-making layer that evaluates the quality of crop row sensor data and selects the appropriate guidance source. When crop row sensors provide reliable data (continuous, undamaged plants), the system uses primary guidance for precise alignment. When gaps or damaged plants are detected, the intermediary switches to secondary guidance using historic path information, maintaining reliability while preserving measurement precision when available
Solution Approach 2:
The system prepares backup guidance capability (secondary guidance using historic path) in advance to cushion against failures of the primary guidance system. This ensures that when plants are missing or damaged and crop row sensors cannot provide reliable data, the vehicle guidance continues without interruption, maintaining both precision and reliability
3Productivity
If the vehicle travels at higher speed, then productivity is improved, but the crop row sensors cannot provide reliable real-time estimates of central position
Solution Approach 1:
The system dynamically adjusts the guidance strategy based on vehicle speed. At lower speeds, primary guidance using real-time crop row sensor data provides precise central position estimation. When vehicle speed increases beyond the reliable sensing threshold, the system dynamically switches to secondary guidance using historic path information, which remains accurate at higher speeds, thus maintaining both productivity and measurement precision across the full speed range
Solution Approach 2:
The system changes the guidance parameter source based on vehicle speed conditions. When high speed is detected, the system transitions from real-time sensor parameters (which become unreliable at high speeds) to historic path parameters (which remain reliable), allowing the vehicle to maintain high productivity while preserving measurement precision through parameter selection
Data Source
AI summary
A method and system for guidance of an off-road vehicle comprises a crop row sensor for sensing position data for one or more crop rows. A primary guidance path of the vehicle is determined based on the sensed position data for the one or more crop rows if there not a material gap in the crop row for the current location of the vehicle. Alternately or cumulatively, a secondary guidance path of the vehicle is determined based on a historic path heading of the vehicle if there is the material gap in a crop row for a current location of the vehicle.