Field Obstacle Mapping for Surface and Subsurface Detection
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Solution Overview
Problem
Agricultural machines face inefficiencies and potential damage due to undetected objects on or beneath the ground, leading to reduced performance and safety hazards, as existing detection systems fail to effectively map and avoid obstacles in real-time.
Innovation Solution
A control system with integrated obstacle detection systems that use multiple sensors to provide detection inputs for objects on and below the surface, allowing for real-time mapping and visualization, and a spotlight system to adjust its position for targeted illumination of detected obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple detection systems are integrated to detect obstacles on and below the ground surface, then measurement precision and reliability of obstacle detection are improved, but device complexity increases
Solution Approach 1:
The detection system is segmented into multiple specialized detection systems, each optimized for detecting obstacles at different depths and positions. This segmentation allows each subsystem to focus on specific detection tasks, improving overall measurement precision while maintaining manageable complexity through modular architecture.
Solution Approach 2:
Multiple detection systems are merged and integrated into a unified control system that processes data from all sensors. This combining approach consolidates the detection capabilities, allowing the system to achieve comprehensive obstacle detection with improved precision while managing complexity through centralized processing.
2Productivity
If real-time obstacle mapping and visualization are implemented, then productivity and safety are improved, but use of energy increases
Solution Approach 1:
The obstacle mapping and visualization is implemented as a periodic process that updates the obstacle map at regular intervals rather than continuously. This periodic action maintains productivity by providing timely obstacle information while reducing energy consumption by allowing the system to enter lower-power states between updates.
Solution Approach 2:
The system uses the work machine's existing movement and operational data to automatically update the obstacle map without requiring additional active sensing during mapping. This self-service approach leverages naturally occurring data from machine operation to maintain productivity while minimizing additional energy expenditure.
3Loss of information
If differentiated visual indicators are assigned to obstacles at different depths, then measurement precision and information quality are improved, but device complexity increases
Solution Approach 1:
Differentiated visual indicators are assigned to represent different obstacle depth characteristics. This local quality differentiation allows the system to convey specific depth information through visual cues without requiring complex additional hardware, as the differentiation is achieved through software-based visual representation.
Solution Approach 2:
The system uses color changes and visual indicator differentiation to represent obstacles at different depths and positions. This approach encodes depth information in the visual display rather than requiring additional physical sensors or complex processing, thereby reducing information loss while maintaining relatively simple system architecture.
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 operational efficiency of agricultural machines by preventing damage from hidden obstacles, improving safety by detecting and avoiding objects in real-time, and optimizing seed placement, thereby reducing yield loss and ensuring safer operations.
Implementation Method 1
The light unit can be coupled to the work machine, and the processor can generate commands to the one or more actuators to adjust a position of the light unit about one or more axes to position the light unit at an orientation that directs a light emitted from the light unit toward the target object.
Data Source
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AI summary
A work machine (100) is disclosed. The work machine (100) comprising: a control system (602, 602a) having an obstacle detection system (1420), a first detection system (1422) of the obstacle detection system (1420) configured to provide a first detection input indicative of a presence of one or more first obstacles (1701) on a surface of a particular field, a second detection system (1424) of the obstacle detection system (1420) configured to provide a second detection input indicative of a presence of one or more second obstacles (1701) that are at least partially below the surface of the particular field, the control system (602, 602a) includes a memory (606) having instructions stored therein that are executable by a processor (608) to cause the processor (608) to receive the first detection input and the second detection input, and to selectively map, with the aid of a location system (644), an obstacle map (1700) identifying a location of each of the one or more first and second obstacles (1701), the processor (608) further configured to assign a first visual indicator (1702) to visually indicate on the obstacle map (1700) the presence of the one or more first obstacles (1701) on the surface of the particular field, and a second visual indicator (1704) to visually indicate on the obstacle map (1700) the one or more second obstacles (1701) are at least partially below the surface of the particular field, the first visual indicator (1702) being different than the second visual indicator (1704). Furthermore, a method of operating the work machine (100 is disclosed.