Agricultural Machine Route Control for Mud-Prone Fields
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Solution Overview
Problem
Self-propelled agricultural machines face impairment due to mud areas in agricultural fields, as existing technologies lack effective methods to anticipate and avoid such conditions during autonomous operation.
Innovation Solution
The control device of the self-propelled agricultural machine adjusts its route based on weather data and topographic map data, using satellite-based position localization systems and sensor devices to detect and adapt to mud-prone areas, allowing the machine to either bypass or process these areas before they become impassable, thereby preventing damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the machine operates autonomously along a predetermined route, then productivity is improved, but the machine may encounter mud areas causing impairment
Solution Approach 1:
The control device receives weather forecast data indicating future rainfall and proactively adjusts the route before mud areas form. By performing route adaptation in advance based on predicted weather conditions, the system prevents machine impairment while maintaining autonomous operation continuity.
Solution Approach 2:
The system continuously monitors weather forecast data and field conditions, using this feedback to dynamically adjust the operating route. The control device compares predicted weather conditions with the current route plan and modifies the route to avoid areas that will become impassable due to rainfall.
2Reliability
If the machine avoids mud areas by adjusting the route, then reliability is improved, but additional time is required for route planning and adjustment
Solution Approach 1:
The system performs route adjustments proactively based on weather forecasts before the machine encounters problematic areas. By anticipating mud formation and pre-calculating alternative routes, the system minimizes downtime and maintains continuous operation without reactive stopping or maneuvering.
Solution Approach 2:
The control device autonomously processes weather forecast data and independently determines route modifications without requiring external intervention. The system self-adjusts the operating route based on predicted conditions, eliminating the need for manual route planning and reducing time loss.
3Productivity
If the machine processes mud-prone areas before they become impassable, then productivity is maintained, but the risk of machine impairment increases
Solution Approach 1:
The system uses weather forecast data to identify areas that will become muddy and adjusts the route to process these areas before rainfall occurs. By proactively cultivating mud-prone fields before they become impassable, the system maintains productivity while preventing machine impairment through timely completion of work in vulnerable areas.
Data Source
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AI summary
The present invention relates to a self-propelled agricultural machine (1) for cultivating an agricultural field (2). The present invention is based on the general idea that a control device (3) of the self-propelled agricultural machine (1) is designed and/or programmed to adapt the route (4) along the agricultural field (2) based on weather data relating to the field (2) to be cultivated and based on topographic map data relating to the field (2) to be cultivated.