Robot Cleaner Position Recognition Using Feature Point Matching
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Solution Overview
Problem
Current robot cleaners lack precise position recognition and efficient path planning, relying on inexpensive control sensors and obstacle detection methods that are not optimized for effective cleaning operations.
Innovation Solution
A robot cleaner equipped with an image detecting unit, feature point extracting and matching units, and a control unit that uses image data to create and match feature points, allowing for precise position recognition and adaptive path correction based on obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an image detecting unit is used for position recognition, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces traditional mechanical control sensors with an image detecting unit (camera) to capture images of feature points. This substitution allows the robot cleaner to recognize its position through image processing and coordinate transformation rather than relying on mechanical sensors, thereby improving measurement precision while managing device complexity through software-based solutions.
Solution Approach 2:
The patent introduces feature points as intermediary elements between the image detecting unit and the position recognition system. By detecting and tracking feature points in the environment, the system creates a reference framework that mediates the relationship between image data and position information, enabling precise position recognition without requiring complex direct measurement systems.
2Measurement precision
If feature point matching is implemented, then position recognition precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary actions by pre-identifying and tracking feature points across multiple images. The control unit continuously captures images and extracts feature point coordinates in advance, maintaining a library of feature point positions that can be quickly referenced for position recognition, thereby reducing real-time processing time while maintaining high precision.
Solution Approach 2:
The system implements feedback by continuously comparing current feature point coordinates with previously detected coordinates. The control unit uses the matching results between current and historical feature points to calculate position information, creating a feedback loop that refines position recognition accuracy while optimizing processing efficiency through iterative comparison rather than complete re-analysis.
Data Source
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AI summary
Disclosed are a robot cleaner and a method for controlling the same. A plurality of images are detected through an image detecting unit such as an upper camera, and two or more feature points are extracted from the plurality of images. Then, a feature point set consisting of the feature points is created, and the feature points included in the feature point set are matched with each other. This may allow the robot cleaner to precisely recognize a position thereof. Furthermore, this may allow the robot cleaner to perform a cleaning operation or a running operation by interworking a precisely recognized position with a map.