Mobile Work Machine Object Detection for Rear Blind Spots
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Solution Overview
Problem
Mobile work machines face challenges in detecting objects in their rear path due to blind spots, especially when reversing, as existing systems often generate false positives and fail to accurately locate objects, leading to increased risk of collisions.
Innovation Solution
An object detection system that combines radar detection with vision recognition, using image processing to evaluate detected objects and generate control signals to control the machine's movement, thereby improving the accuracy of object detection and reducing false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If radar detection is used to detect objects in the rear path, then the detection range is improved, but false positives increase and measurement precision deteriorates
Solution Approach 1:
The patent combines radar detection with vision recognition systems to merge the strengths of both technologies. The radar provides wide detection range while the vision system provides precise object identification and location verification, thereby maintaining broad coverage while reducing false positives and improving measurement precision through cross-validation of detection data.
Solution Approach 2:
The system implements feedback mechanisms where the vision recognition system validates radar detections by analyzing visual data in the identified regions. This feedback loop allows the system to confirm or reject radar detections, improving object location accuracy and reducing false positives while maintaining the radar's extensive detection range.
2Measurement precision
If vision recognition is used to evaluate detected objects, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary action by using the radar to first identify potential object locations and regions of interest before the vision recognition system processes images. This preliminary detection narrows down the areas that require detailed visual analysis, improving object evaluation accuracy while reducing the overall computational burden and system complexity compared to full-field vision processing.
Solution Approach 2:
The vision recognition system is applied selectively to specific regions of interest identified by radar detection, rather than processing the entire field of view. This segmentation approach focuses computational resources on relevant areas, improving object evaluation accuracy for detected objects while minimizing the complexity increase from adding vision capabilities.
3Measurement precision
If the system processes images to correlate object locations, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The radar system performs preliminary detection to identify object locations and regions of interest before image processing begins. This preliminary action provides the vision system with targeted coordinates and bounding boxes, allowing it to process only relevant image portions and rapidly correlate object locations with visual data, thereby improving correlation accuracy while minimizing processing time.
Solution Approach 2:
The system applies high-quality image processing and correlation algorithms only to specific local regions of interest identified by radar, rather than processing the entire image uniformly. This local quality approach concentrates computational effort on areas containing detected objects, improving location correlation accuracy for those objects while reducing overall processing time by ignoring irrelevant areas.
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
Enhances the operator's ability to avoid objects by providing accurate location and classification of detected objects, reducing the likelihood of collisions and improving the safety of reversing maneuvers.
Implementation Method 1
a radar configured to transmit a radar signal and receive reflections of the radar signal
Implementation Method 2
evaluating the object by performing image processing of the portion of the image
Data Source
AI summary
A method of controlling a mobile work machine on a worksite includes receiving an indication of an object detected on the worksite, determining a location of the object relative to the mobile work machine, receiving an image of the worksite, correlating the determined location of the object to a portion of the image, evaluating the object by performing image processing of the portion of the image, and generating a control signal that controls the mobile work machine based on the evaluation.