Autonomous ROV Module for Underwater Mapping
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Solution Overview
Problem
Existing remotely operated vehicles (ROVs) require manual control from a surface vessel, limiting their ability to efficiently map large underwater areas and perform tasks autonomously, which can be time-consuming and labor-intensive for human operators.
Innovation Solution
A module that attaches to an ROV, featuring a watertight housing with sensors and a processor that generates navigation plans and control instructions using sensor data, allowing the ROV to autonomously perform underwater tasks without a tether to a surface vessel, utilizing machine learning algorithms and existing interfaces for control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual control from surface vessel is used, then human operators can control ROV, but it is time-consuming and labor-intensive for mapping large underwater areas
Solution Approach 1:
The ROV is equipped with autonomous navigation capabilities including sensors (cameras, LIDAR, sonar), onboard processors, and machine learning algorithms that enable it to independently map underwater areas without continuous human intervention. The system processes sensor data autonomously to generate navigation plans and control instructions, allowing the ROV to perform tasks self-servingly and significantly improving mapping productivity while reducing human operator time
Solution Approach 2:
The patent replaces the mechanical manual control system with an autonomous control system based on electronic sensors, processors, and algorithms. The onboard processor analyzes sensor data and generates control instructions automatically, substituting the mechanical joystick control from surface vessel with an electronic autonomous navigation system that operates independently underwater
2Extent of automation
If autonomous control is implemented, then ROV can perform tasks independently, but requires complex sensors and processing systems
Solution Approach 1:
The patent employs a suite of multi-functional sensors including cameras for visual navigation and inspection, LIDAR for distance measurement and mapping, and sonar for underwater navigation. These sensors serve multiple purposes: navigation, obstacle detection, terrain mapping, and task execution. The onboard processor integrates data from all sensors to generate comprehensive navigation plans, making the system universally applicable to various underwater tasks without requiring task-specific hardware modifications
Solution Approach 2:
The autonomous control system is divided into modular functional components: sensor modules (cameras, LIDAR, sonar), data processing module with machine learning algorithms, navigation plan generation module, and control instruction module. This segmentation allows each component to be optimized independently while working together as an integrated autonomous system, managing complexity through functional decomposition
3Adaptability or versatility
If customized modules are created for various underwater tasks, then task-specific performance improves, but manufacturing and deployment complexity increases
Solution Approach 1:
The patent implements a universal ROV platform equipped with multiple sensor types (cameras, LIDAR, sonar) and an onboard processor capable of running various machine learning algorithms. This universal system can be configured for different underwater tasks through software programming rather than hardware modification. The same physical platform can perform navigation, inspection, mapping, and other tasks by loading appropriate algorithms and sensor configurations, greatly simplifying manufacturing and deployment while maintaining high adaptability
Solution Approach 2:
The system employs dynamic task configuration where the ROV's behavior and functionality are determined by programmable algorithms rather than fixed hardware configurations. The onboard processor can load and execute different machine learning models and navigation algorithms depending on the required task, allowing the system to dynamically adapt to various underwater operations without physical reconfiguration or custom manufacturing
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling a remotely operated vehicle (ROV) for performing an underwater task. One apparatus includes a watertight housing; a mounting hardware that attaches the watertight housing to the ROV; one or more sensors in the watertight housing, the one or more sensors configured to generate sensor data that is associated with an underwater task; and one or more processors in the watertight housing, the one or more processors configured to: receive the sensor data from the one or more sensors; generate a navigation plan for the ROV using the sensor data; determine, using the navigation plan, control instructions configured to control the ROV to perform the underwater task; and provide the control instructions to an interface of the ROV configured to communicate with the apparatus.