Terrain Image Analysis for Mobile Work Machine Hazard Avoidance
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Solution Overview
Problem
Mobile work machines, such as combine harvesters, face operational challenges due to varying terrain conditions like standing water and mud, which can cause the machines to become stuck, and these conditions are often obscured from the operator's view, leading to adverse performance.
Innovation Solution
A method involving the capture and analysis of spectral responses from terrain images to generate an image distance metric compared to a base spectral response model, with control systems adjusting propulsion and steering to navigate safely and avoid adverse conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the operator relies on direct visual observation of terrain conditions, then the operator can see the terrain, but adverse terrain conditions like standing water and mud remain obscured and undetected
Solution Approach 1:
The patent replaces the mechanical/visual observation system with an optical sensing system that captures spectral response images. The imaging device detects terrain conditions through spectral analysis rather than direct visual observation, enabling detection of hidden hazards like standing water and mud that are invisible to the human eye.
Solution Approach 2:
The system transforms terrain detection from visual parameter space to spectral parameter space. By analyzing spectral response across multiple wavelengths, the system identifies terrain conditions based on their unique spectral signatures, converting undetectable visual conditions into detectable spectral measurements.
2Adaptability or versatility
If the machine traverses over terrain with varying soil conditions, then the machine can operate across different field areas, but the machine may encounter standing water or mud that causes it to become stuck
Solution Approach 1:
The system performs preliminary detection of adverse terrain conditions before the machine reaches them. By capturing and analyzing spectral response images of upcoming terrain, the control system identifies hazards in advance and can take preventive actions to avoid getting stuck.
Solution Approach 2:
The system establishes a feedback loop where spectral image analysis continuously monitors terrain conditions ahead of the machine, and the control system adjusts machine operation based on this feedback. This closed-loop control enables real-time adaptation to varying terrain conditions while maintaining reliable operation.
3Loss of information
If spectral image analysis is implemented to detect terrain conditions, then terrain hazards can be detected, but the system complexity increases
Solution Approach 1:
The control system serves multiple functions: it processes spectral images, compares them against stored spectral profiles, determines terrain conditions, and controls machine operation. By making the control system universal and multi-functional, the patent reduces the need for separate dedicated systems for each function, thereby managing complexity while achieving comprehensive terrain detection and control.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the mobile work machine to detect and respond to terrain hazards, preventing getting stuck and ensuring smoother operation by providing real-time alerts and controlling subsystems based on image analysis, thus enhancing operational efficiency and safety.
Implementation Method 1
receiving an image of spectral response at an area of terrain corresponding to a path of the mobile work machine
Data Source
AI summary
A method of controlling a mobile work machine includes receiving an image of spectral response at an area of terrain corresponding to a path of the mobile work machine, generating an image distance metric based on a distance between the spectral response and a base spectral response model corresponding to the terrain, comparing the image distance metric to a distance threshold, and controlling a controllable subsystem of the mobile work machine based on the comparison.