Robot Cleaner Position Recognition Using 3D Feature Point Matching
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Solution Overview
Problem
Current robot cleaners lack precise position recognition and mapping capabilities, relying on inexpensive control sensors that limit their ability to efficiently clean all areas autonomously, especially in complex environments.
Innovation Solution
A robot cleaner equipped with an image detecting unit, feature point extracting and matching units to create 3D coordinates information from 2D feature points, and a control unit that verifies positions using similarity calculations and moving distance measurements, allowing for precise navigation and path correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an image detecting unit with feature point extraction and matching is used, then position recognition precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces traditional mechanical control sensors with an image detecting unit that uses optical fields (cameras) to capture images and extract feature points. This substitution enables precise position recognition through image processing and feature matching algorithms, achieving higher measurement precision while reducing reliance on complex mechanical sensing systems.
Solution Approach 2:
The patent introduces feature points as intermediary elements between the image detecting unit and the position recognition system. By extracting and matching feature points from images, the system creates a bridge that translates visual information into precise position data, resolving the contradiction between using simple sensors and achieving high precision.
2Productivity
If feature point extraction and matching is implemented, then cleaning efficiency in complex environments is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary action by pre-extracting and storing feature points from images before the actual position recognition and path planning processes. This preprocessing step allows the robot to quickly match features during navigation, reducing real-time processing time and improving overall cleaning efficiency in complex environments.
Solution Approach 2:
The system uses itself to generate the data it needs for navigation. The image detecting unit captures images, the feature extraction unit processes them, and the extracted features are immediately used for position recognition and path correction, creating a self-sufficient system that minimizes external processing delays.
3Manufacturing precision
If 3D coordinates information is created from 2D feature points, then mapping accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies dimensionality change by transforming 2D feature points from images into 3D coordinates in the mapping process. This transformation enables accurate three-dimensional mapping and position recognition by adding depth information through coordinate system conversion, achieving high mapping accuracy while managing computational complexity through efficient mathematical transformations.
Data Source
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AI summary
Disclosed are a robot cleaner and a method for controlling the same. The robot cleaner is capable of recognizing a position thereof by extracting one or more feature points having 2D coordinates information with respect to each of a plurality of images, by matching the feature points with each other, and then by creating a matching point having 3D coordinates information. Matching points having 3D coordinates information are created to recognize a position of the robot cleaner, and the recognized position is verified based on a moving distance measured by using a sensor. This may allow a position of the robot cleaner to be precisely recognized, and allow the robot cleaner to perform a cleaning operation or a running operation by interworking the precisely recognized position with a map.