Work Vehicle Obstacle Detection With Speed-Adaptive Camera Cycles
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Solution Overview
Problem
Existing obstacle detection systems in work vehicles suffer from low object discrimination accuracy, particularly when tall grass or floating debris is present, leading to erroneous obstacle detection.
Innovation Solution
Implement a time division system for obstacle discrimination processing using multiple imaging devices, adjusting processing cycles based on vehicle direction and speed, combined with lidar sensors for accurate distance measurement, and integrating image processing with active sensors for precise obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a radar device with low object discrimination accuracy is used as the obstacle detection sensor, then the system configuration is simplified, but the object discrimination accuracy deteriorates leading to erroneous detection of tall grass or floating matter as obstacles
Solution Approach 1:
The image processing is divided into different processing cycles for different imaging devices based on their imaging ranges. Imaging devices whose imaging range includes the travel direction are processed in a first processing cycle, while other imaging devices are processed in a second processing cycle. This segmentation allows the system to maintain high object discrimination accuracy for critical areas without unnecessarily processing all images at maximum detail, thus resolving the contradiction between simplified configuration and accurate detection.
2Speed
If the processing target cycle per unit time is shortened for all imaging devices, then the obstacle detection responsiveness is improved, but the processing load on the single image processing device increases excessively
Solution Approach 1:
Different processing target cycles are assigned to different imaging devices based on their specific imaging ranges and relevance to the travel direction. Imaging devices capturing the travel direction (front and rear cameras) are processed with shorter cycles for higher responsiveness, while side cameras are processed with longer cycles. This local differentiation optimizes responsiveness where needed while managing overall processing load, resolving the contradiction between detection speed and processing capacity.
3Device complexity
If obstacle discrimination processing is performed on all images from all imaging devices with the same processing cycle, then the processing is simplified, but the detection accuracy for obstacles in the travel direction is insufficient
Solution Approach 1:
The processing target cycle is dynamically adjusted based on the travel direction and vehicle speed. When the vehicle is moving, imaging devices whose imaging range includes the travel direction are assigned a first processing cycle with shorter duration for higher accuracy detection. Other imaging devices are assigned a second processing cycle with longer duration. This dynamic adjustment ensures high detection accuracy for critical areas while adapting to changing operational conditions, resolving the contradiction between processing simplicity and detection precision.
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 obstacle detection accuracy by minimizing false positives from tall grass or debris, ensuring timely and sequential processing, and maintaining high precision in obstacle detection even in challenging environments.
Implementation Method 1
a plurality of imaging devices 81 to 84, each of which captures an image of surroundings of the work vehicle
Implementation Method 2
a plurality of active sensors 85A to 85C, each of which measures a distance to a measurement target object present in surroundings of the work vehicle
Data Source
AI summary
The obstacle detection system for a work vehicle enables an obstacle, present in the surroundings of a work vehicle, to be accurately detected. This obstacle detection system for a work vehicle has: a plurality of imaging devices that take images of the surroundings of a work vehicle; and an image processing device that performs, according to a time division system, an obstacle identification process for identifying an obstacle on the basis of the images from the plurality of imaging devices. The image processing device changes a to-be-processed cycle per unit time for the plurality of imaging devices in the time division system in accordance with the vehicle speed and the traveling direction of the work vehicle.