Marine Vessel Proximity Sensing With Most-Important-Object Filtering
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Solution Overview
Problem
Existing proximity sensing systems for marine vessels generate large amounts of data impractical for embedded controllers and bandwidth-limited networks, with insufficient filtering and prioritization methods for autonomous or semi-autonomous navigation.
Innovation Solution
A simplified two-dimensional vessel outline is used to calculate and prioritize proximity measurements, reducing computational load by identifying the most important object dataset, which includes linearly and rotationally closest measurements, and translating data into a common reference frame for navigation control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive proximity measurements are collected from multiple sensors on the vessel, then navigation safety and collision avoidance capability are improved, but data processing complexity and computational load increase significantly
Solution Approach 1:
The patent segments the continuous proximity data stream into discrete angular zones (e.g., 0-45 degrees, 45-90 degrees) relative to the vessel's centerline. Each zone is processed independently to identify closest objects, reducing the computational complexity from analyzing all points globally to processing smaller angular segments, thereby maintaining safety while reducing processing burden on embedded controllers.
Solution Approach 2:
The patent extracts only the most critical proximity measurements - specifically identifying the closest object in each angular zone and prioritizing data from zones closest to the vessel's centerline. This extraction principle filters out redundant data points while preserving the most safety-relevant information, reducing data volume for transmission and processing without compromising collision avoidance capability.
2Measurement precision
If detailed proximity measurement data is transmitted to the control system, then navigation precision is improved, but network bandwidth consumption increases
Solution Approach 1:
The patent extracts and transmits only the essential proximity data - the distance and angle to the closest object in each predefined angular zone, rather than transmitting all raw sensor measurements. This selective extraction maintains navigation precision by preserving the most relevant spatial information while significantly reducing the data volume transmitted over bandwidth-limited marine networks.
Solution Approach 2:
The patent implements partial data transmission by sending processed proximity information for only the most critical angular zones (those closest to the vessel's centerline and path) rather than all zones. This partial action approach transmits sufficient data for safe navigation while conserving network bandwidth, accepting that some peripheral zone data may be omitted when resources are constrained.
3Speed
If real-time processing of all proximity data is performed, then collision avoidance responsiveness is improved, but computational resources on embedded controllers are overwhelmed
Solution Approach 1:
The patent performs preliminary processing of proximity data at the sensor level or edge device, pre-identifying the closest object in each angular zone and calculating relevant parameters before transmission. This preliminary action reduces the computational burden on the embedded controller to merely comparing pre-processed data from different zones, enabling real-time collision avoidance responsiveness while staying within the limited computational resources of embedded marine controllers.
Solution Approach 2:
The patent segments the proximity analysis into independent angular zone evaluations, where each zone's closest object is determined separately through simple comparison operations. This segmentation allows parallel processing of multiple zones without requiring complex global optimization algorithms, achieving real-time performance on embedded controllers by breaking down the computationally intensive task into many simple, independent zone assessments.
Data Source
AI summary
A navigation system for a marine vessel incudes one or more proximity sensors, each at a sensor location on the marine vessel and configured to measure proximity of objects in an area surrounding the marine vessel and generate proximity measurements, and a control system configured to receive the proximity measurements measured by the one or more proximity sensors. From the received proximity measurements, four linearly-closest proximity measurements to the marine vessel are identified, including one closest proximity measurement to the marine vessel in each of a positive X direction, a negative X direction, a positive Y direction, and a negative Y direction. A most important object (MIO) dataset is generated identifying the four linearly-closest proximity measurements and propulsion of the marine vessel is controlled based at least in part on the MIO dataset.