Underwater Vehicle Route Simulation for Bottom-Close Navigation
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Solution Overview
Problem
In underwater vehicle navigation, existing technologies face challenges in setting an optimal route that allows the vehicle to approach the underwater bottom while avoiding collisions, especially in complex topographies, due to weakened signal reflection and multipath issues, leading to unreliable height measurements and degraded data quality.
Innovation Solution
A route setting method that simulates underwater navigation using a dynamic model and submarine topography data to optimize target depths and attitudes, updating these values based on an objective function to minimize differences with allowable heights and achieve optimal navigation states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the underwater vehicle is controlled to be close to the underwater bottom to obtain high resolution data, then the data quality and resolution are improved, but the risk of bottom collision increases
Solution Approach 1:
The system performs preliminary simulation of the underwater navigation route using a dynamic model and submarine topography data before actual navigation. This preliminary action allows the system to predict the vehicle's trajectory and adjust target depths in advance to avoid bottom collision while maintaining close proximity for high-quality data collection.
Solution Approach 2:
The system uses feedback from the simulation results to iteratively update target depth values. The simulated navigation route provides information about potential collisions, which is fed back to adjust the target depth settings, creating a closed-loop control system that balances data quality and collision avoidance.
2Reliability
If the target depth is set to make the underwater vehicle separated from the underwater bottom by a sufficient distance to avoid bottom collision, then the safety is improved, but the quality of data obtained from the underwater bottom and the resolution are remarkably degraded
Solution Approach 1:
The system dynamically adjusts target depth values at different waypoints based on the simulated navigation route and local topography. Rather than using a fixed safety distance, the target depth is optimized for each segment of the route, allowing the vehicle to be closer to the bottom where safe and farther where risky, thus maintaining both safety and data quality.
Solution Approach 2:
The system changes the target depth parameter iteratively based on simulation results. By adjusting this key parameter according to the simulated trajectory and topography data, the system finds the optimal balance between safety distance and data collection quality for each navigation segment.
3Ease of operation
If the target depth is set to make the underwater vehicle appropriately separated from the underwater bottom on the basis of experience and intuition, then the navigation is simplified, but the optimality of the navigation route is compromised
Solution Approach 1:
The system performs self-optimization by automatically simulating navigation routes and adjusting target depths based on objective criteria rather than relying on operator experience. The dynamic model and simulation process enable the system to find optimal routes autonomously, improving route optimality while maintaining ease of operation through automated decision-making.
Data Source
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AI summary
The present invention enables navigation control of an underwater vehicle by setting an optimum underwater navigation route with respect to a reference. The route setting method is provided with: an underwater waypoint input step S12 for inputting underwater waypoints of the underwater vehicle; a target value setting step S 14 for setting initial target values at the underwater waypoints; an underwater navigation simulation step S22 for simulating an underwater navigation route of the underwater vehicle by using water bottom topography data and the target values on the basis of a dynamics model of the underwater vehicle; and a target value update step S28 for updating the target values on the basis of an objective function which is calculated on the basis of the underwater navigation route obtained through the simulation in the underwater navigation simulation step S22. Optimum target values are derived by repeating the underwater navigation simulation step S22 and the target value update step S28.