Marine Vessel Vision Calibration Monitoring for 3D Sensor Drift
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Solution Overview
Problem
Existing marine vessel vision systems face challenges in accurately calibrating multiple cameras to ensure precise three-dimensional location determination and navigation, leading to potential miscalibration that can compromise autonomous navigation features.
Innovation Solution
A system comprising multiple cameras with associated three-dimensional coordinate systems and hardware processors that determine calibration health metrics by calculating error distances and generating alerts when miscalibration exceeds a threshold, disabling autonomous navigation features if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple cameras are used to determine three-dimensional location information for navigation, then navigation precision is improved, but calibration complexity increases
Solution Approach 1:
The system continuously monitors calibration health by comparing three-dimensional location information from multiple cameras and generates calibration alerts when discrepancies exceed thresholds. This feedback mechanism detects drift or miscalibration in real-time, allowing the system to maintain precision without requiring complex manual recalibration procedures.
Solution Approach 2:
The vision system performs self-diagnosis by automatically calculating calibration health metrics and generating alerts when calibration degradation is detected. The system monitors its own calibration status using the overlapping field of view between cameras, eliminating the need for external calibration equipment or complex calibration procedures.
2Reliability
If autonomous navigation features are disabled due to miscalibration, then navigation reliability is improved, but operational productivity decreases
Solution Approach 1:
The system selectively disables only the autonomous navigation features when calibration issues are detected, while potentially maintaining other vessel operations. This partial action approach ensures safety-critical navigation functions are protected while minimizing impact on overall operational productivity.
Solution Approach 2:
The calibration monitoring system provides continuous feedback on calibration health status, enabling timely alerts and corrective actions. This feedback loop prevents navigation operations under miscalibrated conditions, maintaining reliability while allowing full productivity when calibration is healthy.
Data Source
AI summary
A system for monitoring calibration of a vision system on a marine vessel is provided, comprising: a processor configured to: receive a plurality of error metrics, each indicative of a degree of miscalibration between a pair of depth sensors, wherein each of the depth sensors is configured to determine three-dimensional position information of features in an environment of the marine vessel; calculate a calibration health metric based on the plurality of error metrics; determine that the calibration health metric is indicative of at least a threshold degree of miscalibration of at least one of the pair of depth sensors; and generate a calibration alert.