Method of detecting a difference in level of a surface in front of a robotic cleaning device
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Solution Overview
Problem
Robotic vacuum cleaners often get stuck on obstacles like doorsteps or thick rugs, and fail to detect ledges, which can result in damage when they fall down stairs.
Innovation Solution
A method and device for detecting differences in level using structured light, where a robotic cleaning device illuminates the surface, captures images, identifies luminous sections, and determines the positional relationship between them to calculate the height of differences, allowing for timely navigation and avoidance of obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If prior art robotic vacuum cleaners use basic obstacle detection, then they can navigate simple surfaces, but they get stuck on obstacles like doorsteps or thick rugs and fail to detect ledges
Solution Approach 1:
The patent transitions from 2D image capture to 3D surface reconstruction by introducing structured light illumination. The system projects light patterns onto the surface and analyzes the deformation of these patterns to calculate depth information, effectively adding a third dimension (height/depth) to the detection capability. This allows the robot to detect ledges and obstacles that were invisible in 2D images while maintaining reasonable system complexity.
Solution Approach 2:
The patent introduces structured light as an intermediary between the camera and the surface. Instead of relying solely on passive light reflection, the system actively illuminates the surface with known light patterns and uses the distortion of these patterns as a mediator to infer surface geometry. This intermediary enables reliable depth detection without requiring complex active sensors like time-of-flight cameras.
2Measurement precision
If the robotic cleaner uses advanced detection methods to identify ledges and obstacles, then detection accuracy improves, but the device complexity and computational requirements increase
Solution Approach 1:
The patent performs preliminary actions by projecting structured light patterns onto the surface before capturing the image. This pre-illumination with known patterns allows the system to encode depth information directly into the captured image, eliminating the need for complex post-processing algorithms. The depth calculation is simplified because the light pattern deformation directly corresponds to surface height variations.
Solution Approach 2:
The patent changes the illumination parameter from uniform or ambient light to structured light patterns with specific geometric configurations. This parameter change transforms the detection problem from one requiring complex 3D sensing to one solvable through 2D image analysis of light pattern deformation. The structured light parameters (pattern geometry, wavelength, intensity) are optimized to maximize measurement precision while minimizing processing requirements.
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
Enables the robotic device to plan its movement and avoid obstacles by determining the height of surfaces and objects, preventing damage and ensuring efficient cleaning by controlling brush movements.
Implementation Method 1
illuminating the surface with light, capturing an image of the surface, detecting a luminous section in the captured image caused by the light
Data Source
Figure 1~2b
Figure 2c
Figure 3
AI summary
The invention relates to a method of detecting a difference in level of a surface in front of a robotic cleaning device, and a robotic cleaning device performing the method. In a first aspect of the invention, a method for a robotic cleaning device (10) of detecting a difference in level of a surface (31) in front of the robotic cleaning device moves is provided. The method comprises illuminating (S101) the surface with light (30b), capturing (S102) an image (40b) of the surface, detecting (S103) a luminous section in the captured image (40b) caused by the light (30b), identifying (S104) at least a first segment (30b') and a second segment (30b'') representing the detected luminous section, and detecting (S104), from a positional relationship between the identified first and second segment (30b', 30b''), the difference in level of the surface (31).