Agricultural Machine Control via Spatial Sensor Overlay
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Solution Overview
Problem
Agricultural machines face challenges in optimizing work parameters due to varying field conditions, with existing methods suffering from reaction time delays, reliance on operator expertise, and incomplete sensor data, leading to sub-optimal performance in precision farming.
Innovation Solution
A control system that spatially models sensor data from agronomic and machine parameters to establish consistent zones for predictive control of machine settings and ground speed, integrating spatial and temporal control techniques to improve responsiveness to field variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If sensor-based automatic adjustment is used, then machine parameter adaptation is automated, but reaction time delay occurs due to sensor evaluation and actuator response
Solution Approach 1:
The system performs preliminary mapping of field properties (soil composition, topography, shadowing) before the actual agricultural operation. This pre-acquired spatial information is stored and used to predict optimal machine parameters in advance, eliminating the need for real-time sensor evaluation and actuator response during operation.
Solution Approach 2:
The system creates a digital copy or map of the field's physical properties using GPS-based positioning and pre-survey data. This virtual representation allows the control system to retrieve pre-determined optimal parameters based on the machine's current position, bypassing real-time sensing delays.
2Extent of automation
If field mapping is performed in advance, then machine parameter control can be automated based on position, but an additional first operation is required to create the map
Solution Approach 1:
The system integrates multiple functions into a single operational pass: it simultaneously performs the agricultural task (seeding, cultivating, harvesting) while acquiring and storing spatial property data for future use. The same machine and sensors used for the primary task are leveraged to create the field map, eliminating the need for separate mapping operations.
Solution Approach 2:
The agricultural machine performs self-mapping during its normal operation. As the machine traverses the field executing its primary function, it autonomously collects spatial data about field properties and stores this information for future reference, without requiring external assistance or separate operations.
3Adaptability or versatility
If topographical properties are used for control, then operator input is required to learn relations, but this limits utilization of parameters beyond human recognition
Solution Approach 1:
The system replaces operator-based learning and decision-making with automated computational algorithms. Instead of relying on human operators to recognize patterns and determine optimal parameters, the system uses computer processing to analyze spatial data and calculate optimal machine settings based on pre-established relationships between field properties and performance outcomes.
Solution Approach 2:
The control system acts as an intermediary between field conditions and machine parameters, using computational algorithms to translate spatial property data into optimal operational settings. This intermediary processing layer enables the system to utilize parameters and relationships that are beyond human recognition capabilities.
Data Source
AI summary
A system and method of controlling an agricultural machine includes successively recording signals from a first sensor sensing an agronomic parameter of a field during an operation of the machine in the field. The system and method of controlling an agricultural machine also includes successively recording signals from a second sensor sensing an operation parameter of the machine during the operation of the machine in the field. The signals of the first sensor and the second sensor are spatially overlaid. A respective zone in the field is determined from the overlaid signals. An actuator of the machine is controlled dependent on the determined zone in which the machine operates.