Automated Sail Path Determination for Marine Vessel Fleet Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current marine seismic survey methods require manual adjustment of sail paths to avoid obstacles, leading to suboptimal computations and increased operational expenditures, especially in multi-vessel operations where synchronization and collision avoidance are challenging.
Innovation Solution
An automated method determines sail paths by minimizing a cost function that includes terms for path length, straight segment length, and penalization of distance to obstacles, using curvilinear geometric forms to encompass detected obstacles and optimize vessel turns, eliminating the need for human operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual adjustment of sail paths is used to avoid obstacles, then vessels can navigate around obstacles, but computational optimality deteriorates and operational expenditures increase
Solution Approach 1:
The system performs self-navigation by automatically computing sail paths that avoid obstacles without human intervention. The automated path planning system uses cost function minimization to generate optimal routes, enabling the vessel to serve its own navigation needs while maintaining computational efficiency and reducing operational expenditures.
Solution Approach 2:
The patent replaces manual mechanical navigation with an automated computational system. Instead of human operators manually adjusting sail paths, the system uses algorithmic optimization with cost functions to automatically compute and adjust navigation paths, substituting human mechanical operations with automated computational processes.
2Reliability
If manual adjustment of sail paths is used to avoid obstacles, then vessels can navigate around obstacles, but operational expenditures increase
Solution Approach 1:
The automated system independently manages obstacle avoidance without requiring human operators, thereby eliminating the operational expenditures associated with manual navigation adjustments. The system optimizes fuel consumption and operational costs by computing efficient paths automatically.
Solution Approach 2:
The system dynamically adjusts navigation parameters by minimizing a cost function that incorporates multiple factors including distance, time, and fuel consumption. This parameter optimization enables the vessel to avoid obstacles while simultaneously reducing operational expenditures through mathematically optimal path selection.
3Productivity
If automated path planning is implemented, then computational efficiency improves, but system complexity increases
Solution Approach 1:
The patent replaces complex manual navigation procedures with a streamlined automated computational system. While the underlying algorithm involves cost function minimization, the overall system complexity is managed by substituting human operational complexity with a unified automated decision-making framework that improves computational efficiency.
4Loss of energy
If automated path planning is implemented, then operational expenditures decrease, but system complexity increases
Solution Approach 1:
The automated navigation system independently optimizes operational expenditures through self-service path planning. The system manages its own navigation decisions using cost function minimization, reducing operational expenditures while containing system complexity through automated decision-making that eliminates the need for human operational intervention.
Solution Approach 2:
The system optimizes multiple parameters simultaneously including path length, travel time, and fuel consumption by minimizing a comprehensive cost function. This multi-parameter optimization reduces operational expenditures while the modular structure of the cost function approach manages system complexity through systematic parameter integration.
5Productivity
If cost function minimization is used to optimize sail paths, then path optimality improves, but collision risk with obstacles increases without proper penalization
Solution Approach 1:
The system optimizes path parameters by minimizing a cost function that includes a penalization term specifically designed to maintain safe distances from obstacles. This parameter modification ensures that path optimality is achieved while collision risk is controlled through the mathematical penalization mechanism embedded in the cost function.
Solution Approach 2:
The cost function provides continuous feedback on the vessel's distance to obstacles, dynamically adjusting the optimal path to maintain safe margins. The penalization term acts as a feedback mechanism that prevents the optimization process from selecting paths that would bring the vessel too close to obstacles, thereby ensuring collision avoidance while maintaining path optimality.
Data Source
AI summary
A method is provided for determining a sail path of vessels on a map representative of a marine geographic area, to perform a turn between a start point and an end point, each vessel having a turn radius, the start point, respectively the end point, being associated with a start, respectively an end, circle, the sail path being curvilinear and composed of arcs and straight segments. The method includes: detecting obstacles likely to interfere with at least one vessel; encompassing obstacles into a curvilinear geometric form; determining a sail path of the vessel by minimizing, under constraints, a cost function comprising: a first term representative of the length of arcs making up the sail path and a second term representative of the length of straight segments making up the sail path, taking into account the start and end circles and the curvilinear geometric forms, and a third term of penalization of distance separating the sail path to be determined, at any point of the sail path, and at least one disturbing object.