Agricultural Machine Coordination via Dynamic Virtual Work Hierarchies
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Solution Overview
Problem
Existing agricultural work machine groups, particularly those with a master-slave hierarchy, lack flexibility and efficiency in optimizing machine parameters for diverse agricultural conditions, leading to suboptimal performance under complex field conditions.
Innovation Solution
Implementing a method where self-optimizing agricultural work machines communicate via a wireless network, forming a virtual work machine with dynamic hierarchies, allowing for collective optimization of machine parameters based on shared sensor data and work process data, and enabling flexible distribution of optimization tasks to enhance overall efficiency and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a master-slave hierarchy is used to control agricultural work machines, then efficiency gains are achieved for machines with clear hardware hierarchy, but flexibility is lost for groups of self-optimizing machines
Solution Approach 1:
The patent transforms the static master-slave hierarchy into a dynamic system where any work machine can become a master or slave depending on real-time conditions. The control relationship is no longer fixed by hardware configuration but dynamically adjusted based on sensor data, work progress, and environmental factors, enabling both efficiency and flexibility
2Ease of operation
If individual work machines optimize their own subsystems independently, then each machine can adjust its parameters, but overall optimization taking into account all interrelationships becomes practically impossible due to high complexity
Solution Approach 1:
The patent merges the optimization capabilities of individual work machines into a collective optimization system. The master work machine aggregates sensor data from all machines and coordinates their optimization actions, combining individual autonomous capabilities with centralized coordination to achieve overall system optimization that considers all interrelationships
3Loss of information
If sensor data is collected only by individual work machines, then each machine has independent data, but the quantity and quality of sensor data available for optimization is limited
Solution Approach 1:
The master work machine serves multiple functions: it acts as a normal work machine performing its own tasks while simultaneously functioning as a data aggregation center and coordination hub for the entire group. This multi-functionality enables comprehensive data collection without adding separate dedicated data collection infrastructure
Data Source
AI summary
A method for executing an agricultural work process on a field by means of a group of agricultural work machines. The work machines each have work assemblies which are adjustable with machine parameters for adapting to the respective agricultural conditions. The work machines of the group communicate with one another via a wireless network. The work machines of the group are configured as self-optimizing work machines which each have a driver assistance system for generating and adjusting machine parameters in an automated manner. These machine parameters are optimized with respect to the agricultural conditions. The work machines of the group cooperate collectively in the manner of a virtual work machine.