Vehicle Turn Path Selection for Sharp Field Turns
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Solution Overview
Problem
Existing agricultural vehicle guidance systems struggle to accurately navigate sharp turns in fields, often requiring manual intervention or backup maneuvers, which can lead to inefficiencies and gaps in field coverage.
Innovation Solution
The system automatically identifies sharp turns in a guidance path, selects a turn pattern from predetermined patterns based on coverage area, and generates navigation instructions to execute the turn pattern, ensuring the vehicle can traverse the turn without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle uses a fixed minimum turning radius for all turns, then the turning maneuver is simple to execute, but gaps appear in the field coverage pattern
Solution Approach 1:
The system dynamically selects from multiple predetermined turn patterns (e.g., 4-point turn, 3-point turn, pivot turn) based on real-time conditions such as vehicle orientation, field contour, and headland area constraints. This dynamic adaptation allows the vehicle to maintain continuous field coverage while executing turns of varying complexity, resolving the contradiction between operational simplicity and coverage accuracy.
2Reliability
If the vehicle requires manual intervention for sharp turns, then the turn execution is reliable, but productivity decreases due to operator input requirements
Solution Approach 1:
The autonomous vehicle independently determines and executes the appropriate turn pattern by evaluating environmental conditions and vehicle state without human intervention. The system self-selects from predetermined turn patterns based on real-time sensor data, maintaining reliable turn execution while eliminating the need for operator input, thus preserving productivity.
3Manufacturing precision
If the vehicle uses multiple predetermined turn patterns, then the field coverage accuracy improves, but the device complexity increases
Solution Approach 1:
The system changes operational parameters by selecting different predetermined turn patterns (each with defined geometry and maneuver steps) based on evaluated conditions. This approach achieves high field coverage accuracy without requiring complex real-time path planning algorithms, as the system chooses from a library of pre-optimized turn patterns rather than generating new paths dynamically.
4Reliability
If the vehicle executes backup maneuvers for turns, then the turn reliability improves, but the time required for operations increases
Solution Approach 1:
The system performs preliminary evaluation of turn conditions before execution, selecting the most appropriate predetermined turn pattern in advance. By pre-assessing factors such as vehicle orientation, field contour, and headland constraints, the system chooses an optimal turn pattern that ensures reliable completion while minimizing execution time, avoiding unnecessary backup maneuvers.
Data Source
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AI summary
Methods, apparatus, and articles of manufacture to generate a turn path for a vehicle are disclosed. An example apparatus disclosed herein includes input interface circuitry to obtain a guidance path for a vehicle, turn identification circuitry to identify a turn in the guidance path, and turn pattern selection circuitry to select, from a plurality of predetermined turn patterns, a turn pattern for the turn, wherein the turn pattern satisfies a condition.