Multi-Sensor Non-Crop Object Detection Near Machine Headers
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Solution Overview
Problem
Existing image-based systems for detecting non-crop objects and work machine conditions in agriculture fail to accurately detect objects in close vicinity to the work machine and miss detection of certain machine conditions.
Innovation Solution
Implementing image-based detection systems with optical sensors and other sensors to monitor and detect non-crop objects and work machine conditions, utilizing processors to analyze sensor data for object recognition and machine condition assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image-based detection systems are used to detect non-crop objects and work machine conditions, then detection capability is provided, but detection accuracy for objects in close vicinity and certain machine conditions deteriorates
Solution Approach 1:
The patent combines multiple sensor types (optical sensors, radar sensors, lidar sensors, ultrasonic sensors) into a unified detection system. This multi-sensor fusion approach allows the system to detect objects and machine conditions with higher accuracy by cross-validating data from different sensor modalities, thereby resolving the contradiction between providing detection capability and achieving reliable detection accuracy.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives data from multiple sensors and processes it through a controller to generate unified detection results. This intermediary processing mechanism filters false positives and enhances detection reliability by synthesizing information from different sensor sources before final object and condition identification.
2Measurement precision
If multiple sensors are deployed to improve detection accuracy, then detection capability improves, but device complexity increases
Solution Approach 1:
The patent implements a universal detection platform where a single controller manages multiple sensors with different functions (optical, radar, lidar, ultrasonic). This multi-functional architecture allows the system to detect various object types and machine conditions using one integrated control unit, reducing overall system complexity while maintaining high detection accuracy through diverse sensor capabilities.
Solution Approach 2:
The patent segments the detection system into modular sensor units, each responsible for specific detection tasks (e.g., optical sensors for visual detection, radar for distance measurement). This segmentation allows independent optimization of each sensor module while maintaining coordinated operation through the controller, thereby managing system complexity through modular design.
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 accuracy of detecting non-crop objects and work machine conditions, enabling timely adjustments to prevent machine interference and damage.
Implementation Method 1
one or more optical sensors positioned to sense and locate objects
Implementation Method 2
The work machine may include radar sensors, optical sensors, lidar sensors, ultrasonic sensors, and any other suitable sensors
Implementation Method 3
The work machine may include radar sensors, optical sensors, lidar sensors
Implementation Method 4
The work machine may include radar sensors, optical sensors, lidar sensors, ultrasonic sensors
Data Source
AI summary
Example apparatuses systems and methods are provided herein. In some examples, a system or method may be provided to determine a presence of one or more objects disposed in of a portion of an agricultural field disposed about a vicinity of a header of the work machine, determine one or more features of the one or more objects, determine whether the one or more objects are desired objects based at least in part on the one or more features of the one or more objects, determine one or more object identifiers of the one or more objects, and transmit instructions to one or more systems to adjust performance of the agricultural machine based at least in part on the one or more object identifiers.