Autonomous Farm Robot Row Allocation for Stable Trajectory Control
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Solution Overview
Problem
Existing solutions for autonomous agricultural robots in Precision Land Management (PLM) require processing a large number of parameters and variables to calculate optimal trajectories, which can lead to instability and inappropriate solutions due to acquisition errors and interdependencies between data.
Innovation Solution
A method for controlling autonomous agricultural robots that transmits periodic row allocation messages and calculates trajectories using constrained optimization, minimizing the number of necessary data points and allowing real-time corrective actions to maintain optimal trajectory monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large number of parameters and variables are processed to calculate optimal trajectories, then the precision of trajectory calculation is improved, but the stability of the system deteriorates due to acquisition errors and interdependencies between data
Solution Approach 1:
The patent extracts and isolates only the essential parameters needed for trajectory calculation, removing unnecessary variables that cause interdependencies and acquisition errors. By taking out only the critical data points required for constrained optimization, the system achieves both precision and stability without processing excessive parameters.
2Manufacturing precision
If complex trajectory calculation methods are used, then the precision of maneuver alignment is improved, but the computational complexity increases
Solution Approach 1:
The patent changes the approach from processing many variables to optimizing a constrained set of key parameters. By transforming the calculation methodology to focus on essential parameters with defined constraints, the system achieves high maneuver alignment precision while reducing computational complexity.
3Speed
If real-time corrective actions are implemented, then the responsiveness of trajectory monitoring is improved, but the system complexity increases
Solution Approach 1:
The patent implements feedback mechanisms that provide real-time corrective actions for trajectory monitoring. By using feedback from essential parameter measurements, the system achieves rapid responsiveness while avoiding the complexity of processing extensive data sets, as feedback is based on the minimized set of critical parameters.
Data Source
AI summary
The invention relates to a method for control by a supervisor of at least one autonomous agricultural robot comprising geolocation means, the supervisor transmitting periodic row allocation messages to the at least one autonomous agricultural robot, each of the agricultural robots comprising a computer for controlling the movement of the corresponding robot as a function, on the one hand, of the allocated trajectory and, on the other hand, of the geolocation data, as well as for calculating a row change trajectory as a function of the messages transmitted by the supervisor.