Sweeping robot obstacle avoidance treatment method based on free move technology
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Solution Overview
Problem
Current sweeping robots lack sufficient obstacle avoidance capabilities, leading to reduced operational stability and flexibility, limiting their broader application and user satisfaction.
Innovation Solution
A sweeping robot obstacle avoidance method utilizing a six-axis gyroscope as a signal sensor and left-right wheel electric quantity as auxiliary signals, employing a Mahalanobis distance calculation and sample comparison method to accurately identify and classify four states (collision, obstacle-free, over-threshold, and obstacle pushing) and control operations to prevent blockages, with a three-layer neural network for enhanced classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional obstacle avoidance methods are used, then the robot can perform basic navigation, but the obstacle avoidance accuracy and operational stability are insufficient
Solution Approach 1:
The patent segments the obstacle avoidance function into multiple independent detection components: six-axis gyroscope for motion state detection, grating signal sensor for position detection, and left-right wheel electric quantity sensors for differential drive detection. Each sensor independently monitors specific parameters, and their results are integrated through Mahalanobis distance calculation to achieve comprehensive obstacle avoidance with high reliability and precision
Solution Approach 2:
The patent replaces traditional mechanical obstacle detection methods with electronic sensing systems. Instead of mechanical contact sensors, it uses a six-axis gyroscope to detect motion state changes, grating signal sensors for position feedback, and electrical current monitoring for wheel slip detection. This substitution enables non-contact, high-precision obstacle detection and classification
2Measurement precision
If multiple sensors are added to improve detection accuracy, then the obstacle identification precision increases, but the device complexity increases
Solution Approach 1:
The patent makes the six-axis gyroscope serve multiple functions: it detects collision states, threshold crossing states, and pushing obstacle states all through motion parameter analysis. The grating signal sensor simultaneously provides position information for navigation and obstacle detection. This multi-functionality reduces the need for separate dedicated sensors for each detection task, managing system complexity while maintaining high measurement precision
Solution Approach 2:
The patent merges the data processing of multiple sensors into a unified Mahalanobis distance calculation framework. Instead of processing sensor data separately, it combines gyroscope six-axis data, grating signal position data, and wheel electric quantity data into a single integrated classification system. This merging approach manages complexity by providing a unified analysis method rather than separate processing chains
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
The method achieves an accuracy of over 96% in identifying operational states, ensuring the robot can navigate freely without getting blocked, improving stability and obstacle avoidance efficiency by 60% and detraction efficiency by 50% compared to mechanical detection methods.
Implementation Method 1
a six-axis gyroscope as a signal sensor
Data Source
AI summary
The present disclosure provides a sweeping robot obstacle avoidance treatment method based on free move technology, step 1 and step 2 are as following. Step 1: predetermining a sweeping robot provided with a six-axis gyroscope, a grating signal sensor, and a left-and-right-wheel electric quantity sensing unit. Step 2: performing a real-time sensing and data acquisition on an operation state of the sweeping robot by utilizing the six-axis gyroscope, the grating signal sensor, and the left-and-right wheel electric quantity sensing unit to obtain a real-time data information.