Coordinated Underwater Vehicle Groups for Adaptive Data Acquisition

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Solution Overview

Problem

Current methods for monitoring underwater environments are inadequate for exploring unknown zones and monitoring habitat evolution due to limitations in depth, cost, and coverage, with existing systems struggling to provide high-quality data in diverse and hostile conditions.

Innovation Solution

A method involving coordinated underwater motorized vehicles equipped with sensors, which deploy in a first mission to gather initial data and adjust subsequent mission parameters based on real-time data acquisition, allowing for efficient data collection in varying underwater conditions and areas of different sizes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Area of stationary object

If satellite imagery is used for underwater monitoring, then coverage area is improved, but depth capability deteriorates (unsuitable for depths greater than 20 meters)

Engineering Contradiction:
Improvecoverage areaVSAvoiddepth capability
Core Design Contradiction:
Area of stationary objectVSReliability

Solution Approach 1:

The system divides the monitoring task into two stages: a first mission using multiple vehicles for broad area coverage and a second mission for focused detailed monitoring. This segmentation allows the system to achieve both wide coverage and deep monitoring capability by allocating different vehicle groups to different functional roles.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The first group of vehicles acts as an intermediary that performs initial data collection and transmits information to the second group of vehicles. This intermediary role enables the second group to adjust their trajectories and focus on areas of interest, thereby achieving deep monitoring capability while maintaining overall coverage.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Reliability

If acoustic systems are used for deeper monitoring, then depth capability is improved, but measurement precision deteriorates (less precise for depths greater than 100 meters)

Engineering Contradiction:
Improvedepth capabilityVSAvoidmeasurement precision
Core Design Contradiction:
ReliabilityVSMeasurement precision

Solution Approach 1:

The monitoring area is segmented into broad coverage zones (first mission) and focused detailed zones (second mission). By dividing the task, the system can use acoustic systems for deep area mapping while deploying vehicles closer to specific targets for high-precision measurements, thus resolving the precision-depth tradeoff.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The trajectory patterns are dynamic and adaptive. The second group of vehicles adjusts their trajectories in real-time based on data from the first mission, allowing them to dynamically reposition for optimal measurement precision at various depths rather than following fixed static patterns.

Inventive Principle:
Principle #15Dynamics

3Measurement precision

If divers or underwater equipment are deployed, then measurement precision is improved, but coverage area deteriorates (do not allow for coverage of large areas)

Engineering Contradiction:
Improvemeasurement precisionVSAvoidcoverage area
Core Design Contradiction:
Measurement precisionVSArea of stationary object

Solution Approach 1:

The system segments the monitoring function across multiple vehicles in two groups. The first group covers large areas with broad trajectories, while the second group focuses on specific areas of interest with precision trajectories. This segmentation allows both large-scale coverage and detailed precision monitoring to occur simultaneously.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The vehicles are designed to be multi-functional, capable of performing both broad area mapping and detailed precision monitoring. The same type of vehicle can operate in different roles (first group or second group) depending on the mission phase and requirements, providing universal capability across different operational modes.

Inventive Principle:
Principle #6Universality (Multi-functionality)

4Area of stationary object

If multiple vehicles are deployed for comprehensive monitoring, then coverage area is improved, but device complexity increases

Engineering Contradiction:
Improvecoverage areaVSAvoiddevice complexity
Core Design Contradiction:
Area of stationary objectVSDevice complexity

Solution Approach 1:

The fleet is segmented into two groups with distinct, simplified roles. The first group handles broad area coverage with standardized trajectories, while the second group handles detailed monitoring. This functional segmentation simplifies the control architecture compared to managing a single homogeneous fleet for all tasks, as each group has specialized, less complex control requirements.

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP3333540B1Method and system for acquiring analysis data in an observation area of an underwater environment
Publication Date: 2020.05.13 KOPADIA
  • EP3333540B1 patent drawingFigure 1~3
  • EP3333540B1 patent drawingFigure 4(a)~4(b)
  • EP3333540B1 patent drawingFigure 5~6

AI summary

The present invention relates to a method for acquiring analytical data in an observation zone of an underwater environment comprising at least two missions, a first acquisition mission and a second acquisition mission, conducted simultaneously. Each mission includes the deployment of a group (G1, G2) of underwater motorized vehicles (11, 21, 31; 12, 22, 32), and is defined by a set of mission parameters comprising a trajectory pattern, at least one type of analytical data to be acquired, and operating parameters relating to the sensors of the group capable of acquiring data corresponding to said at least one type of analytical data to be acquired.The set of parameters associated with the second mission is conditioned on results obtained during or following the first mission by the fact that at least one of the mission parameters for the second mission is a function of at least one of the analysis data acquired during the first mission.