Pipe Inspection Robot Sensor Fusion for Accurate Digital Twin Mapping
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Solution Overview
Problem
Conventional techniques for pipeline examination in water and sewer infrastructure rely on human intervention, leading to errors and inefficiencies, and lack the ability to accurately detect features and perform operations like cutting within the environment.
Innovation Solution
A robotic system equipped with multiple sensors, including LIDAR, stereo vision cameras, and infrared cameras, fused with AI models to create accurate digital maps and control operations, enabling precise detection and cutting of pipes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional techniques with human intervention are used for pipeline examination, then operators can directly observe and detect features, but the process is susceptible to errors and lacks efficiency
Solution Approach 1:
The system enables automated detection where the robotic tool independently identifies features and defects using multiple sensors and AI models, eliminating reliance on human operators for real-time detection while maintaining high accuracy and improving inspection efficiency
Solution Approach 2:
The patent replaces human mechanical observation with an automated sensing system comprising LIDAR, infrared cameras, and visual cameras that capture and process data through electronic and optical mechanisms, substituting human intervention with machine-based detection
2Measurement precision
If multiple sensors are used to detect features and temperature variations, then detection capability is improved, but the data remains disjointed and cannot be correlated
Solution Approach 1:
The system merges data from multiple independent sensors (LIDAR for spatial mapping, infrared cameras for temperature, visual cameras for appearance) into a unified digital map, combining previously disjointed data streams into a correlated multi-dimensional representation of the pipeline environment
Solution Approach 2:
The robotic tool is designed with multi-functional sensors that can detect various physical quantities (spatial position, temperature, visual features) simultaneously, enabling a single system to perform multiple detection functions and integrate their data into a comprehensive model
3Productivity
If automated detection systems are implemented, then efficiency is improved, but the ability to perform operations like cutting within the environment is lacking
Solution Approach 1:
The robotic tool is designed as a universal platform that performs both detection functions (using multiple sensors) and operational functions (cutting, drilling, or other interventions), enabling the same system to both inspect and modify the pipeline environment
Solution Approach 2:
The system performs preliminary detection and mapping operations to identify features and defects, then uses this information to guide subsequent operational actions such as cutting, ensuring that operations are performed accurately based on prior automated detection
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides high-accuracy mapping and operational capabilities within enclosed spaces, reducing errors and enhancing efficiency in pipeline inspections and maintenance processes.
Implementation Method 1
one or more LIDAR sensors configured to provide LIDAR data
Implementation Method 2
Other systems utilize infrared cameras to detect temperature variations within the scanned environment
Data Source
AI summary
A robot sized and shaped for reception in a pipe, the robot including a chassis configured for movement of the robot in the pipe, a plurality of sensors including an inertial measurement unit (IMU), an encoder and a stereo vison camera associated with the robot, and a sensor fusion system operable to combine readings from the IMU, the encoder and the stereo vision camera to determine a position of the robot within the pipe, and wherein the sensor fusion system is operable to use machine learning in creating a digital twin of the pipe.