Self-propelled robot voice labeling internal map
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Solution Overview
Problem
Existing self-propelled robots, such as vacuum cleaners, face difficulties in easily positioning place names on their internal maps, as the process is tedious and prone to human error, especially with increasing numbers of locations, and the internal maps may not clearly represent the user's living environment.
Innovation Solution
A self-propelled robot with an orientation sensor system and programming device that allows users to communicate place names verbally, eliminating the need for a graphical interface, where the robot determines its position and assigns the name to the internal map using sensors and neural networks, and provides feedback for accurate placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If graphical user interface controls are used for positioning location names, then the internal map can be labeled, but the process becomes cumbersome and complex for the user
Solution Approach 1:
The patent replaces the mechanical graphical interface interaction (touchscreen controls, drag-and-drop operations) with a voice-based acoustic interface. The user simply speaks the location name, and the system automatically processes it through speech-to-text conversion and assigns it to the current robot position, eliminating the need for complex graphical manipulation while maintaining labeling functionality.
Solution Approach 2:
The system automatically determines the robot's current position using its orientation sensor system and internal map, then automatically assigns the spoken location name to that position without requiring the user to manually navigate graphical interfaces or select positions. The robot serves itself by autonomously completing the labeling task based on voice input alone.
2Adaptability or versatility
If the number of place names increases in the internal map, then more locations can be identified, but the process of labeling becomes more tedious and error-prone
Solution Approach 1:
The system provides immediate feedback to the user by repeating the recognized location name back through the acoustic interface, allowing the user to verify accuracy in real-time. This feedback loop enables quick correction of recognition errors and confirms successful labeling, maintaining high reliability even as the number of labeled locations increases.
Solution Approach 2:
By replacing manual graphical labeling with automated voice recognition and speech-to-text conversion, the system eliminates human errors associated with manual input (typos, wrong selections). The automated processing consistently and accurately assigns location names to positions, scaling reliably regardless of the total number of locations in the map.
3Productivity
If manual positioning of location names is required, then precise control is possible, but the process consumes more time and user effort
Solution Approach 1:
The robot continuously maintains awareness of its current position in the internal map through its orientation sensor system before the labeling action occurs. This preliminary positioning information is ready in advance, so when the user speaks a location name, the system can immediately assign it to the correct position without requiring the user to manually navigate or search for the location, dramatically reducing labeling time.
Solution Approach 2:
The robot autonomously handles all positioning and assignment operations automatically. The user simply provides the location name through voice input, and the robot's programming device self-services by determining the current position from its internal map and completing the assignment, eliminating the time-consuming manual operations previously required.
Data Source
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AI summary
The invention relates to a self-driving robot with an orientation sensor system for creating and maintaining an internal map (60) based on image and/or map data and a programming device, wherein the programming device is designed and configured to receive a command signal containing a location designation (20a-20h) before, after and/or during positioning of the self-driving robot at a location; to determine a position (30a-30h) of the self-driving robot corresponding to the location in the internal map (60); and to assign the location designation (20a-20h) to the determined position (30a-30h) in the internal map (60).