Method for correcting determination threshold of floor medium and method of detecting thereof
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Solution Overview
Problem
Existing floor medium detection methods in robots, such as those using sound sensors, face inaccuracies due to mechanical aging and environmental noise changes, as the preset thresholds set at the factory are not adaptable to varying robot states over time.
Innovation Solution
A method for correcting the determination threshold of a floor medium using a mobile robot equipped with a sound emitter and receiver, where the robot transmits and receives sound signals at specific frequencies to determine and adjust the threshold based on amplitude and frequency domain transformations, ensuring accurate detection by adapting to the current machine state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a preset determination threshold is used for floor medium detection, then the detection method is simple and easy to implement, but the detection accuracy deteriorates over time due to mechanical aging and environmental noise changes
Solution Approach 1:
The patent applies dynamics by transitioning from a static preset threshold to a dynamic adaptive threshold. The threshold is automatically adjusted based on real-time environmental noise levels and mechanical aging characteristics. The system continuously monitors the operating state and modifies the determination threshold accordingly, ensuring accurate floor medium detection throughout the robot's operational life without requiring manual recalibration.
Solution Approach 2:
The patent implements feedback by using the detected floor medium results to continuously optimize the determination threshold. The system compares the preset threshold with actual detection outcomes and environmental noise levels, then adjusts the threshold to minimize detection errors. This closed-loop feedback mechanism ensures that the threshold adapts to changing conditions while maintaining detection simplicity.
2Measurement precision
If the determination threshold is adjusted to adapt to machine aging, then the detection accuracy is improved, but the system complexity increases
Solution Approach 1:
The patent applies self-service by enabling the system to automatically adjust its own determination threshold without external intervention. The robot autonomously monitors its mechanical aging state and environmental noise levels, then self-corrects the threshold parameters. This self-service capability improves detection accuracy while avoiding the complexity of manual calibration systems or external adjustment mechanisms.
Solution Approach 2:
The patent implements parameter changes by dynamically modifying the determination threshold based on measurable physical parameters such as noise level amplitude and frequency characteristics. The system changes the threshold parameter in response to detected variations in environmental noise and mechanical aging indicators, achieving accurate detection through parameter adaptation rather than structural complexity.
3Measurement precision
If frequency domain transformation is used for detection, then the detection accuracy is improved, but the processing time and computational complexity increase
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing frequency domain transformation results for different floor medium types under various aging conditions. Instead of performing full frequency domain transformations in real-time, the system uses pre-computed spectral signatures to rapidly compare against current sensor data. This preliminary preparation significantly reduces processing time while maintaining high detection accuracy.
Solution Approach 2:
The patent implements partial action by performing frequency domain transformation only on critical frequency bands that are most indicative of floor medium types. Rather than analyzing the entire frequency spectrum, the system focuses computational resources on the most informative frequency ranges, achieving accurate detection with reduced processing time and computational complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method improves the accuracy of floor medium detection by dynamically adjusting the threshold to account for mechanical aging and noise changes, reducing incorrect determinations and enhancing the robot's ability to identify carpets and hard floors effectively.
Implementation Method 1
collects sound reflected by a floor medium and generated when a main brush and a fan within a robot operate through a sound sensor
Implementation Method 2
according to differences of absorption effects of a carpet on harmonic waves of different frequency bands in a sound signal
Data Source
AI summary
A method for correcting a determination threshold of a floor medium and a method of detecting thereof are provided. The method is used for controlling a mobile robot equipped with a sound emitter and a sound receiver to detect and recognize the floor medium during a movement just started. A first detection result of a current floor medium is obtained by actively transmitting and receiving a sound signal, then, a to-be-adjusted detection result of the current floor medium is obtained only by passively receiving the sound signal through the sound receiver, and according to the similarity/difference of the two detection results, the determination threshold is corrected in the case of passively receiving the sound signal, so that the to-be-adjusted detection result is determined to be consistent with the first detection result.