Automated Landmark Tagging for Robotic Navigation
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Solution Overview
Problem
Current robotic navigation systems rely on primitive methods and require persistent landmarks for localization, which are time-consuming and costly to survey, and lack the capability to identify and distinguish landmark persistence or position stability.
Innovation Solution
A system and method for identifying landmarks in images using a worksite features database, user interface, and data processing system that analyzes images to determine suggested identities, confirms them, and stores confirmed identities and attributes, enabling accurate landmark identification and localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual survey methods are used to identify and localize landmarks, then measurement precision can be achieved, but loss of time and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical surveying methods with an automated optical system. A camera captures images of the worksite, and image processing algorithms automatically identify and localize landmarks. This substitution of mechanical manual work with optical automation significantly reduces survey time while maintaining measurement precision through computer vision techniques.
Solution Approach 2:
The system enables self-service landmark identification by allowing the mobile robotic device to autonomously capture images, process them through algorithms, and automatically identify landmarks without human intervention. The device serves itself by performing the entire landmark survey process independently, eliminating the need for time-consuming manual surveys while achieving accurate localization.
2Measurement precision
If manual survey methods are used to identify and localize landmarks, then measurement precision can be achieved, but cost increases become prohibitive
Solution Approach 1:
The patent replaces expensive manual surveying equipment and professional surveyor services with an automated optical system using standard cameras and computer vision algorithms. This substitution dramatically reduces implementation costs while maintaining measurement precision, making the technology economically viable for widespread deployment in autonomous navigation applications.
Solution Approach 2:
The system creates digital copies (images) of physical landmarks and processes these copies through algorithms to identify and localize landmarks. This copying approach eliminates the need for expensive physical surveying equipment and manual measurement tools, significantly reducing costs while achieving the same measurement precision through image analysis.
3Productivity
If automated image analysis is used to identify landmarks, then productivity increases, but device complexity increases
Solution Approach 1:
The patent employs a universal image processing framework that can identify multiple types of landmarks (natural features, artificial structures, vegetation) using the same camera and algorithmic approach. This multi-functional system handles diverse landmark types without requiring separate specialized equipment for each type, managing complexity while maintaining high productivity across various worksite environments.
Solution Approach 2:
The system introduces an intermediary layer of image processing algorithms that mediate between the simple camera input and the complex task of landmark identification. These algorithms serve as intermediaries that automatically perform feature detection, classification, and localization, enabling high productivity while managing system complexity through modular software architecture rather than complex hardware.
Data Source
AI summary
The different illustrative embodiments provide a method for identifying landmarks in an image. An image of a worksite is received. The image is analyzed to determine a suggested identity of a worksite feature in the image. The suggested identity of the worksite feature is sent over a communications unit. A confirmation of the suggested identity of the worksite feature is received to form a confirmed identity. The confirmed identity and a number of attributes associated with the confirmed identity is stored in a database.