Mobile Robot Home Appliance Mapping Using Image-Based Deep Learning
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Solution Overview
Problem
Mobile robots face challenges in determining the position and type of home appliances within a traveling area, which hinders their ability to effectively communicate and remotely control these appliances for user convenience and situational control.
Innovation Solution
A mobile robot equipped with an image acquisition unit and a controller that performs deep learning to identify home appliances based on images, generating a map that indicates the type, position, and controllability of appliances, allowing for remote control based on user input and acquired information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the mobile robot uses traditional obstacle detection methods to navigate the traveling area, then the robot can avoid obstacles and move autonomously, but the robot cannot identify home appliances and their positions for remote control functionality
Solution Approach 1:
The image acquisition unit and image processing algorithms serve multiple functions: they detect obstacles for navigation, identify home appliance types through pattern recognition, and determine appliance positions for mapping. This multi-functional approach enables the robot to perform both navigation and home appliance identification using the same hardware and software resources, thereby improving adaptability without proportionally increasing system complexity
2Loss of information
If the mobile robot equips an image acquisition unit and deep learning system to identify home appliances, then the robot can determine appliance types and positions, but the device complexity and computational requirements increase
Solution Approach 1:
The system pre-processes images to extract key features and pre-trains deep learning models with appliance data before deployment. By performing preliminary actions such as feature extraction and model training in advance, the robot reduces the computational burden during actual operation, enabling accurate appliance identification while managing processing system complexity
Solution Approach 2:
The robot creates a digital map that copies and represents the physical traveling area, including the positions and types of home appliances. This virtual representation allows the system to store and process appliance information efficiently without requiring continuous complex image analysis, thereby reducing ongoing computational requirements while maintaining complete appliance information
3Loss of information
If the mobile robot generates a detailed map with home appliance information, then the robot can provide intuitive appliance arrangement visualization, but the data processing and storage requirements increase
Solution Approach 1:
The system extracts only the essential information needed for appliance identification and positioning from the full images, such as appliance type labels and coordinate positions. By extracting only the necessary data elements and discarding redundant image details, the robot creates a compact appliance map that provides complete appliance arrangement information while minimizing data volume for storage and processing
Data Source
AI summary
Disclosed is a mobile robot for determining a type and position of a home appliance present within in a traveling area and controlling the home appliance according to a control command or a situation. The mobile robot includes a controller for determining the type and position of the home appliance positioned within the traveling area based on the image acquired through an image acquisition unit, and for generating and outputting a home appliance map that is a traveling area map on which at least one of the type or position of the home appliance is indicated, wherein the home appliance is remotely controlled according to a control command of a user, a situation is determined according to the acquired information without a control command, and a home appliance appropriate for a specific situation is controlled.