Surface Roughness Estimation for Off-Road Steering Gain Control
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Solution Overview
Problem
Off-road vehicles face challenges in maintaining accurate steering and application of crop inputs due to ground surface irregularities, which can lead to deviations from target paths and increased operator fatigue, despite the use of automatic guidance systems.
Innovation Solution
A method and system that estimates surface roughness by detecting motion and attitude data using sensors and location-determining receivers, calculating a surface roughness index, and adjusting steering gain settings to align with varying terrain conditions, thereby improving steering control and input application precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If automatic guidance systems are used to guide the vehicle to track a path plan, then steering precision is improved, but ground surface irregularities still cause unwanted deviations in heading or yaw
Solution Approach 1:
The system performs preliminary detection of ground surface irregularities using motion sensors and attitude data before the vehicle encounters them. By calculating a surface roughness index in advance and mapping it to the field, the guidance system can proactively adjust steering parameters to compensate for upcoming irregularities, preventing deviations before they occur rather than reacting to them after the fact.
Solution Approach 2:
The system continuously collects motion data, attitude data, and position information from sensors, processes this data to determine surface roughness characteristics, and feeds this information back to dynamically adjust steering gain parameters. This closed-loop feedback mechanism allows the guidance system to adapt to varying ground conditions in real-time, maintaining tracking reliability despite surface irregularities.
2Manufacturing precision
If steering gain is increased to improve path tracking accuracy, then steering precision is improved, but vehicle instability increases on rough terrain
Solution Approach 1:
The system divides the field into multiple zones based on surface roughness characteristics and assigns different steering gain parameters to each zone. Instead of using a uniform high steering gain across the entire field, the system applies locally optimized gain values that are appropriate for each specific terrain condition, maintaining both tracking accuracy and vehicle stability in different areas.
Solution Approach 2:
The steering gain parameter is made dynamic rather than static, allowing it to change automatically based on real-time detection of surface roughness conditions. The system continuously adjusts the steering gain level according to the current terrain characteristics, increasing gain when needed for accuracy and decreasing it when stability becomes compromised, creating an adaptive balance between the two competing requirements.
3Measurement precision
If motion sensors and attitude data are collected continuously to estimate surface roughness, then measurement precision is improved, but energy consumption increases
Solution Approach 1:
The system collects motion and attitude data at optimized sampling intervals rather than continuously, using the minimum necessary frequency to achieve adequate measurement precision for surface roughness estimation. This partial action approach captures sufficient terrain variation information while avoiding the excessive energy consumption of truly continuous data collection.
Solution Approach 2:
The field is divided into discrete zones with characteristic surface roughness properties, and data collection intensity can be adjusted by zone. The system segments the measurement process to focus computational and sensing resources on areas where surface variations most impact steering, reducing overall energy consumption while maintaining measurement precision where it matters most for path tracking.
Data Source
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Figure 2A
AI summary
A method and system for estimating surface roughness of a ground for an off-road vehicle to control steering of a vehicle, an implement, or both, comprises detecting motion data of an off-road vehicle traversing a field or work site during a sampling interval. A first sensor is adapted to detect pitch data of the off-road vehicle for the sampling interval to obtain a pitch acceleration. A second sensor is adapted to detect roll data of the off-road vehicle for the sampling interval to obtain a roll acceleration. An electronic data processor or surface roughness index module determines or estimates a surface roughness index based on the detected motion data, pitch data and roll data for the sampling interval. The surface roughness index can be displayed on the graphical display to a user or operator of the vehicle.