Underwater Vehicle Pose Estimation via Sensor Fusion
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Solution Overview
Problem
Current methods for estimating the position and orientation of underwater vehicles lack the necessary precision for navigating complex underwater structures, such as offshore platforms and natural formations, often resulting in inaccurate navigation and control.
Innovation Solution
A method and system that combines data from a vehicle navigation system and a 3D sonar sensor to generate a fused pose estimate, using a Bayesian Combiner to correlate and update the position and orientation of the underwater vehicle, allowing for high-precision scanning and navigation of underwater structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current sensor-based methods are used for position and orientation estimation, then the system is simple to operate, but the measurement precision is insufficient for high-precision navigation
Solution Approach 1:
The patent combines data from multiple sources (vehicle navigation system and 3D sonar sensor) into a fused pose estimate using a Bayesian Combiner. This merging of independent estimation systems allows the vehicle to achieve high-precision position and orientation data by integrating complementary information from different sensors, resolving the contradiction between measurement precision and device complexity.
2Reliability
If single-source pose estimation is used, then the device complexity is low, but the reliability of navigation data is insufficient for complex underwater environments
Solution Approach 1:
The system implements a feedback mechanism where the Bayesian Combiner continuously integrates pose estimates from the vehicle navigation system and 3D sonar sensor, using the correlated sensor data to refine and update the fused pose estimate. This feedback loop ensures high reliability of navigation data by constantly correcting and validating position and orientation information against multiple independent sources.
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
This approach provides a high-precision estimation of the underwater vehicle's position and orientation, enabling accurate navigation and control, even in complex environments, with the ability to correct drift and provide real-time updates, suitable for applications like inspection, repair, and manipulation of underwater structures.
Implementation Method 1
The other source is a sonar based sensor that is configured to provide three dimensional images of underwater structures
Data Source
AI summary
A method and system are described that can be used for combining two sources of position and orientation (pose) information where the information from one source is correlated with the information from the other and the sources produce information at differing rates. For example, the method and system allow for estimating position and orientation (pose) of an underwater vehicle relative to underwater structures by combining pose information computed from a 3D imaging sonar with pose information from a vehicle navigation system. To combine the information from the two sources, a determination is made as to whether to generate a forward prediction of the pose estimate of one of the sources relative to the other, and generating the forward prediction if needed. An updated pose of the underwater vehicle is determined based on the fused pose estimate, and which is used for vehicle guidance and control.