Robot Cleaner Image-Based Room Recognition for Global Localization
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Solution Overview
Problem
Robot cleaners face challenges in accurately returning to their charging base and recognizing their position on a map when their location is changed by external factors, leading to inefficient battery recharging and mapping issues due to lack of global localization capabilities.
Innovation Solution
The implementation of a control method that uses image acquisition and feature distribution learning to estimate room-specific feature distributions, allowing the robot cleaner to recognize its current position by comparing acquired images with stored reference groups, thereby determining its location within a cleaning area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot cleaner uses infrared signal sensing to search for the charging base, then it can detect the charging base signal, but it cannot accurately recognize its position on the map when moved to a new location, leading to inefficient battery recharging
Solution Approach 1:
The patent creates a map copy of the cleaning area that includes position information of the charging base and other features. When the robot needs to return to the charging base, it uses this stored map copy to determine its position and navigate directly, rather than searching for infrared signals. This allows accurate position recognition even when moved to a new location, resolving the contradiction between measurement precision and time loss.
Solution Approach 2:
The robot performs preliminary mapping of the cleaning area before actual cleaning operations. During this preliminary action, it stores position information of the charging base and creates a reference map. When moved to a new location, this pre-established map enables immediate position recognition and direct navigation to the charging base, eliminating the need for time-consuming signal searching.
2Loss of information
If the robot cleaner creates a map of the cleaning area, then it can store position information, but it fails to recognize its current position on the map when its location is changed by external factors
Solution Approach 1:
The patent implements feedback mechanisms where the robot continuously compares its current sensor data with the stored map information. When its location changes, the system receives feedback about the mismatch between expected and actual positions, then updates its position recognition accordingly. This feedback loop enables the robot to maintain position information retention while adapting to location changes.
Solution Approach 2:
The position recognition system is designed to be dynamic rather than static. When the robot detects that its location has changed (through sensor data mismatch or user intervention), the system dynamically updates its position estimate by comparing current environmental features with the stored map. This dynamic adaptation allows the robot to maintain accurate position information even when moved to new locations.
3Reliability
If the robot cleaner searches for the infrared signal at the current position, then it can detect the charging base signal by chance, but it runs out of battery while wandering around searching for the signal
Solution Approach 1:
The robot performs preliminary mapping that includes storing the position of the charging base in the cleaned area map. When battery recharging is needed, it uses this pre-stored position information to navigate directly to the charging base without wandering or searching for infrared signals. This preliminary action ensures reliable charging base detection while minimizing battery consumption by eliminating unnecessary movement.
4Adaptability or versatility
If the robot cleaner is moved to another room by the user, then it can be repositioned for different cleaning tasks, but it cannot recognize its position on the existing map or previously created map
Solution Approach 1:
The system maintains a copy of the cleaning area map that includes positional information of features like the charging base. When the robot is moved to another room or new location, it uses this map copy to recognize its position by comparing current environmental features with the stored map data. This copying mechanism enables the robot to adapt to repositioning while maintaining accurate position recognition.
Data Source
AI summary
A control method for a robot cleaner includes acquiring a plurality of images of surroundings during travel of the robot cleaner in a cleaning area, estimating a plurality of room-specific feature distributions according to a rule defined for each of a plurality of rooms, based on the images acquired while acquiring the plurality of images, acquiring an image of surroundings at a current position of the robot cleaner, obtaining a comparison reference group including a plurality of room feature distributions by applying the rule for each of the plurality of rooms to the image acquired while acquiring the image at the current position, comparing the obtained comparison reference group with the estimated room-specific feature distributions, and determining a room from the plurality of rooms having the robot cleaner currently located therein.