Agricultural Machine Path Planning Across Fields and Roads
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Solution Overview
Problem
Current path planning systems for agricultural machines performing self-driving lack efficiency in navigating between fields and on roads, particularly in handling obstacles and dynamic environmental conditions.
Innovation Solution
A path planning system that includes a processor and storage for generating and adjusting paths based on maps of fields and roads, integrating work plans and real-time sensor data to enable efficient self-driving, obstacle avoidance, and adaptive route adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the agricultural machine uses a simple path planning system, then the device complexity is reduced, but the productivity and efficiency of navigation between fields and on roads deteriorates
Solution Approach 1:
The path planning system is segmented into multiple functional modules: a map generation unit that creates road and field maps, a path planning unit that generates navigation paths, and a control unit that executes the paths. This segmentation allows each module to specialize in specific tasks, improving overall navigation efficiency while keeping individual module complexity manageable
Solution Approach 2:
The system performs preliminary actions by generating detailed road and field maps before navigation begins, and by pre-calculating optimal paths between fields based on the maps. This advance preparation enables the agricultural machine to navigate efficiently without real-time computation delays during actual travel
2Adaptability or versatility
If the agricultural machine travels only within fields, then the path planning is simpler, but the adaptability to handle obstacles and dynamic environmental conditions on roads deteriorates
Solution Approach 1:
The path planning system is designed with multi-functionality to handle both field-based agricultural work and road-based transportation. The map generation unit creates comprehensive maps that include both field boundaries and road networks, while the path planning unit can generate paths for both contexts, allowing the system to adapt to various operational environments without requiring separate specialized systems
Solution Approach 2:
The system incorporates dynamic adaptability by continuously monitoring the agricultural machine's position using GPS and adjusting the navigation path in real-time based on actual environmental conditions, obstacles encountered, and changing operational requirements, whether in fields or on roads
3Adaptability or versatility
If the agricultural machine performs both field work and road travel, then the versatility of the system is improved, but the loss of time for path planning and navigation increases
Solution Approach 1:
The system performs preliminary path planning by pre-calculating optimal routes between multiple fields and along road networks before the agricultural machine begins operation. The map generation unit creates comprehensive navigation data in advance, allowing the path planning unit to quickly determine routes without time-consuming real-time calculations during field-to-road transitions
Solution Approach 2:
The system incorporates feedback mechanisms where the agricultural machine's actual position, speed, and operational status are continuously monitored and fed back to the path planning unit. This real-time feedback allows the system to adjust paths dynamically based on actual conditions, optimizing travel time between fields and on roads while maintaining operational versatility
Data Source
AI summary
A path planning system for an agricultural machine performing self-driving includes a storage to store a map including fields and a road around the fields, and a processor to generate a path for the agricultural machine on the map. The processor is configured or programmed to generate a first path along which the agricultural machine is to travel while performing agricultural work in any of the fields, the first path being generated on the corresponding field on the map, and generate a second path along which the agricultural machine is to travel toward the field, the second path being generated on the road on the map.