Vacuum cleaner and control method therefor
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Solution Overview
Problem
Conventional robot cleaners face challenges in precisely detecting obstacles and determining if they can pass through spaces due to their reliance on 2D image information, leading to reduced accuracy and increased computation demands when using 3D camera sensors.
Innovation Solution
A robot cleaner equipped with a 3D camera sensor that samples coordinates information at multiple heights, generates lattice maps, and adjusts its driving path based on detected shapes and spaces, allowing it to react promptly to obstacles and improve position sensing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a 3D camera sensor is used to acquire 3D coordinates information, then obstacle detection precision is improved, but computation amount increases excessively
Solution Approach 1:
The patent segments the 3D coordinate information by dividing the spatial space into multiple height layers. The controller samples coordinates only at specific height levels rather than processing all 3D points, thereby reducing computation while maintaining detection precision for obstacles at those critical heights.
Solution Approach 2:
The patent applies partial action by sampling only a subset of 3D coordinates at predetermined heights rather than processing the complete 3D coordinate set. This partial sampling approach reduces computation load while still providing sufficient information for obstacle detection and navigation decisions.
2Device complexity
If 2D image information is used for obstacle detection, then computation amount is reduced, but detection precision of distance and stereoscopic shape is lowered
Solution Approach 1:
The patent transitions from 2D image information to 3D coordinates information acquired by a 3D camera sensor. This dimensional upgrade enables precise distance measurement and stereoscopic shape detection by incorporating depth information (Z-axis) in addition to the 2D plane coordinates, thereby resolving the precision limitations of 2D sensing.
3Loss of information
If feature points are extracted from 2D image information, then obstacle information can be detected, but accuracy is significantly lowered when feature points are difficult to extract
Solution Approach 1:
The patent uses 3D coordinates information from a 3D camera sensor instead of relying on feature point extraction from 2D images. The 3D coordinate data provides direct spatial information about obstacles including distance and shape, eliminating the need for complex feature point extraction and associated accuracy losses when features are indistinct.
Data Source
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AI summary
Disclosed is a cleaner which performs an autonomous driving, comprising: a cleaner body; a driving unit configured to move the cleaner body; a camera configured to detect 3D coordinates information; and a controller configured to sample a part of detected 3D coordinates information based on at least one preset height, and configured to control the driving unit based on the sampled coordinates information.