Mining Obstacle Detection Using State-Based Radar Thresholds
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Solution Overview
Problem
Mining work machines operating on off-road surfaces with bumps and potholes face challenges in accurate obstacle discrimination due to vehicle body jolting and height differences, leading to false detection of non-obstacles as obstacles and vice versa, when using obstacle detection techniques designed for paved roads.
Innovation Solution
A mining work machine equipped with a peripheral detection sensor, speed sensor, and obstacle discrimination device that filters obstacle information based on travel state and reflection intensities to differentiate between obstacles and non-obstacles, using distance and reflection intensity thresholds adjusted according to the vehicle's state, ensuring accurate detection of obstacles for collision avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If a millimeter wave radar is mounted on the vehicle body of a mining work machine, then the detection range is extended, but the vehicle body jolting on bumpy road surfaces causes the radar to shake, radiating detection waves from oblique directions and reducing detection accuracy
Solution Approach 1:
The patent applies dynamics by making the detection thresholds dynamic rather than static. The distance threshold and reflection intensity threshold are adjusted based on the vehicle's travel state (stopped, starting, or normal traveling). This allows the system to adapt to the changing detection conditions caused by vehicle jolting, maintaining accurate obstacle discrimination despite the radar shaking on bumpy surfaces.
2Area of stationary object
If the millimeter wave radar is installed at an elevated position to accommodate the greater height of mining work machines, then the detection coverage is improved, but the radiation area becomes smaller and reflection intensity from obstacles decreases
Solution Approach 1:
The patent applies parameter changes by adjusting the reflection intensity threshold based on the vehicle's travel state. When the vehicle is stopped or starting, a lower reflection intensity threshold is used to compensate for the reduced reflection intensity caused by the elevated radar position. This ensures that obstacles near the vehicle can still be detected with sufficient sensitivity despite the smaller radiation area.
3Device complexity
If general automotive obstacle discrimination techniques are applied to mining work machines, then the implementation is simplified, but the accuracy decreases due to different road conditions and vehicle characteristics
Solution Approach 1:
The patent applies local quality by implementing state-specific threshold values tailored to the particular conditions of mining work machines. Instead of using a single universal threshold, the system employs different distance thresholds and reflection intensity thresholds for different travel states (stopped, starting, normal traveling). This localized approach ensures high accuracy in obstacle discrimination for each specific operating condition of mining work machines on off-road surfaces.
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
The solution enhances the accuracy of obstacle discrimination for mining work machines, reducing false detections and improving collision avoidance by tailoring the detection technique to the unique conditions of off-road environments, thereby minimizing unnecessary stops and brake operations.
Implementation Method 1
a peripheral detection sensor that radiates an electromagnetic wave forward in a traveling direction, receives reflected waves from each obstacle candidate, detects reception intensities of the reflected waves
Implementation Method 2
receives reflected waves from each obstacle candidate
Data Source
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AI summary
An obstacle determination device mounted on an own vehicle determines whether the state of the own vehicle is a state immediately after progressing or a normal travel state ; selects, as a distance threshold provided to determine a non-obstacle, a starting distance threshold if in the state immediately after starting, or a normal distance threshold if in the normal travel state; extracts obstacle candidates on the basis of the result of comparison of the distance at which an obstacle candidate was initially detected with the distance threshold; selects a starting reflection intensity threshold if the state immediately after starting , or a normal reflection intensity threshold if in the normal travel state; excludes non-obstacles on the basis of the result of comparison of the reception strength of the reflection wave of the remaining obstacle candidates with the reflection intensity threshold; and outputs the remaining obstacle candidates as obstacles.