Active Terrain Mapping for Mobile Machine Height Control
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Solution Overview
Problem
Current systems for predicting ground elevation in front of mobile machines, such as combine harvesters, are ineffective, especially when there are deviations in the terrain, leading to inaccurate height control and crop volume calculations due to reliance on projecting a plane based on past elevation measurements without considering changing ground conditions.
Innovation Solution
A system that generates an elevation map by estimating elevation values for points around a mobile machine using a pose detection system, assigning confidence values based on distance, and aggregating these values to control controllable subsystems like header height or boom height, allowing for real-time terrain adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a plane is projected based on past elevation measurements, then the system is simple to operate, but the measurement precision of ground elevation deteriorates when terrain deviates from the projected plane
Solution Approach 1:
The system performs preliminary mapping of the ground surface by collecting elevation measurements at multiple locations and constructing a digital elevation model before the machine reaches those areas. This advance preparation creates an accurate terrain map that can be referenced for height control, eliminating the need for complex real-time plane projections while improving elevation accuracy.
Solution Approach 2:
The system creates a digital copy of the ground surface through point cloud data and elevation maps. This virtual representation of the terrain allows the control system to reference accurate elevation data without requiring complex geometric calculations, effectively copying the terrain information for use in height control algorithms.
2Measurement precision
If active terrain mapping is implemented, then the measurement precision of ground elevation improves, but the device complexity increases due to additional sensors and processing systems
Solution Approach 1:
The system uses a multi-functional approach where the pose detection system serves multiple purposes: it tracks machine position for navigation, determines orientation for accurate mapping, and provides reference data for elevation calculations. This multi-functionality reduces the need for separate dedicated sensors, thereby limiting the increase in device complexity while maintaining high measurement precision.
Solution Approach 2:
The system leverages the machine's own motion and existing sensors to perform terrain mapping. As the machine moves through the field, it automatically collects elevation data at its current position, using its own pose information to georeference the measurements. This self-service approach eliminates the need for external mapping equipment, reducing system complexity while achieving accurate terrain models.
3Adaptability or versatility
If real-time pose detection is used for elevation mapping, then the adaptability to changing terrain conditions improves, but the use of energy increases due to continuous sensor operation and data processing
Solution Approach 1:
The system performs pose detection and elevation mapping at periodic intervals rather than continuously. The control processor collects elevation measurements at regular sampling rates and updates the digital elevation model periodically. This periodic operation maintains real-time adaptability to terrain changes while significantly reducing energy consumption compared to continuous sensing and processing.
Solution Approach 2:
The system maintains continuous accumulation of elevation data as the machine moves through the field, building the digital elevation model progressively. Rather than performing discrete mapping operations, the useful action of terrain mapping continues throughout operation, allowing the system to adapt to terrain changes in real-time while distributing energy consumption over the entire working period rather than concentrating it in brief intensive measurement phases.
Data Source
AI summary
An elevation map generator in a mobile agricultural machine generates an elevation map by estimating an elevation value for points in front of a work machine based on a plane derived from a measured elevation point measured by a pose detection system affixed to the work machine. Each elevation value has a corresponding confidence value that varies inversely with a distance of the point from the pose detection system. As the machine moves, additional elevation values are aggregated for each point, based on the confidence values. The machine is controlled based on the aggregated evaluation values.