Diagonal Distance Sensor Layout for Marine Blind-Spot Mapping
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Solution Overview
Problem
Existing marine vessel mapping systems face high costs, complex integration, persistent blind spots, and challenges in real-time updates, making them inefficient and unsafe for navigation.
Innovation Solution
A simplified sensor arrangement using a bow-mounted and stern-mounted distance sensor diagonally positioned on the vessel, combined with data processing techniques to dynamically update a surroundings map, reducing hardware and computational complexity while enhancing accuracy and completeness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor systems (radar, sonar, LIDAR) are used for mapping surroundings, then measurement precision and coverage are improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts and eliminates unnecessary sensor systems from the traditional multi-sensor approach. By using only a single distance sensor mounted on the bow, the system removes the complexity of integrating radar, sonar, and LIDAR while maintaining effective surroundings mapping capability through selective data collection and processing.
Solution Approach 2:
The single distance sensor on the bow performs multiple functions: it detects obstacles, maps surroundings, and provides navigation data. The processing circuitry universally handles various mapping scenarios (congested waterways, open waters, docking maneuvers) using the same hardware platform, eliminating the need for specialized sensors for each function.
2Measurement precision
If multiple expensive sensors like LIDAR are deployed, then measurement precision is improved, but cost increases prohibitively
Solution Approach 1:
The patent replaces expensive, high-precision sensors like LIDAR with a simpler, more affordable distance sensor. The system accepts that the single sensor has limitations but compensates through intelligent data processing and multiple sensor positions, achieving cost-effective surroundings mapping suitable for vessels with limited budgets.
Solution Approach 2:
Instead of using one expensive LIDAR sensor, the patent uses multiple copies of cheaper distance sensors positioned at different locations on the vessel (bow, stern, and optionally sides). This array of simpler sensors collectively provides comprehensive surroundings coverage that would be prohibitively expensive with high-end sensors.
3Area of stationary object
If traditional sensor systems are used, then coverage is improved, but blind spots persist due to vessel structure and sensor placement limitations
Solution Approach 1:
The patent segments the surroundings mapping task into multiple zones by placing distance sensors at different vessel locations (bow, stern, and optionally sides). Each sensor covers a specific sector, and the processing circuitry integrates these segmented views to create a complete surroundings map, eliminating blind spots that would exist with a single sensor position.
Solution Approach 2:
The patent transitions from single-point sensing to multi-dimensional coverage by distributing sensors across different spatial positions on the vessel. This spatial distribution in multiple dimensions (forward, aft, port, starboard) allows the system to cover the entire surrounding area without blind spots, as each sensor observes from a unique angular perspective.
Data Source
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AI summary
Approaches are disclosed for mapping surroundings of a marine vessel (1). These involve obtaining, at a first location (30), first distance data from distance sensors (10) comprising a bow-mounted sensor (10-1) arranged to monitor a first area (12) involving surroundings adjacent to the bow (2) and a first side (3, 5) of the marine vessel (1), and a stern-mounted sensor (10-2) arranged to monitor a second area (13) involving surroundings adjacent to the stem (4) and a second side (5, 3), opposite the first side (3, 5), of the marine vessel (1). The approaches further involve generating a surroundings map (20) comprising at least two unmapped areas (22-1, 22-2) indicating blind spots of at least partially incomplete surroundings representations; obtaining, at a second location (40), second distance data from the set of distance sensors (10); and causing updates to the unmapped areas (22-1, 22-2) based on the second distance data.