Autonomous Navigation Using Visual Buoy Markers
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Solution Overview
Problem
Current autonomous robot navigation systems rely on expensive sensors like laser scanners and GPS, making them unaffordable for many applications, and visual odometry is computationally challenging, necessitating a more cost-effective and accurate navigation method.
Innovation Solution
The use of visual navigation buoys with predetermined locations, equipped with identity markers and angular degree coding, allows autonomous vehicles to determine their position using high-resolution optical cameras, laser or GPS measurements, and trigonometric calculations, independent of other navigation methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high end sensors like laser scanners and GPS are used for autonomous navigation, then navigation accuracy is improved, but system cost increases
Solution Approach 1:
The patent replaces expensive, durable sensors (laser scanners, GPS) with inexpensive visual markers (buoys) that can be easily deployed and removed. These markers provide accurate navigation data through simple visual detection by the camera system, eliminating the need for costly hardware while maintaining navigation precision.
Solution Approach 2:
The patent substitutes mechanical/optical sensing systems (laser scanners, GPS receivers) with a visual recognition system using standard cameras. The navigation information is encoded in visual markers that can be detected and processed through image analysis, replacing complex mechanical sensing with simpler optical detection and computational processing.
2Device complexity
If visual odometry is used for autonomous navigation, then equipment cost is reduced, but computational difficulty increases
Solution Approach 1:
The patent pre-encodes navigation information (position, orientation, distance data) into visual markers before deployment. This preliminary encoding of measurement data into visual patterns allows the system to extract navigation information directly from images without requiring complex real-time computational geometry or feature matching algorithms.
Solution Approach 2:
The patent introduces visual markers as intermediary objects that carry encoded navigation information. These markers serve as mediators between the physical environment and the navigation system, translating complex spatial relationships into simple visual patterns that can be easily detected and processed by standard camera systems.
3Measurement precision
If visual navigation buoys with encoded information are used, then navigation precision is improved, but marker complexity increases
Solution Approach 1:
The patent uses color variations and visual patterns on markers to encode multiple pieces of navigation information (position, orientation, identity) in a single visual element. Different colors, patterns, or arrangements of visual features represent different data, allowing rich information encoding without adding physical complexity to the marker structure.
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 high accuracy in navigation correction assistance, reducing costs and computational complexity while enhancing navigation precision using visual odometry with predefined landmarks.
Implementation Method 1
A navigation application visually acquires a first navigation buoy with an identity marker
Implementation Method 2
The first distance may also be determined between the vehicle and the first navigation buoy using laser measurement
Data Source
AI summary
A system and method are provided for navigation correction assistance. The method provides a vehicle with a camera and an autonomous navigation system comprising a navigation buoy database and a navigation application. The navigation application visually acquires a first navigation buoy with an identity marker and accesses the navigation buoy database, which cross-references the first navigation buoy identity marker to a first spatial position. A first direction marker on the first navigation buoy is also visually acquired. In response to visually acquiring the first direction marker, a first angle is determined between the camera and the first spatial position. A first distance may also be determined between the vehicle and the first navigation buoy using visual methods or auxiliary position or distance measurement devices. Then, in response to the first spatial position, the first angle, and the first distance, the spatial position of the vehicle can be calculated using trigonometry.