Method and apparatus for controlling robot, electronic device, and computer-readable storage medium
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Solution Overview
Problem
Conventional cleaning robots struggle to accurately distinguish between different types of right angle corner points, leading to incomplete cleaning due to their D-shaped structure and conventional corner detection algorithms.
Innovation Solution
A method and apparatus that utilize environmental mapping, corner detection algorithms, and coordinate system analysis to identify and clean specific right angle corner points, incorporating grayscale analysis and piecewise linear fitting to determine target corner points for precise cleaning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a D-shaped cleaning robot is used to improve corner cleaning coverage, then the cleaning coverage is improved, but the ability to accurately distinguish different types of right angle corner points deteriorates
Solution Approach 1:
The patent segments the corner detection process into multiple stages: initial corner detection, coordinate system establishment, grayscale value analysis of quadrants, and classification into inner/outer corner points. This segmentation allows the system to handle different corner types systematically, resolving the contradiction between comprehensive corner coverage and accurate corner type distinction.
Solution Approach 2:
The patent introduces a coordinate system dimension to analyze corner points. By establishing a coordinate system with the corner point as origin and analyzing grayscale values in different quadrants (spatial dimensions), the system can distinguish between inner and outer corner points. This dimensional approach enables accurate corner type identification while maintaining comprehensive cleaning coverage.
2Device complexity
If conventional corner detection algorithms are used to simplify the detection process, then the device complexity is reduced, but the accuracy of identifying different corner point types deteriorates
Solution Approach 1:
The patent introduces intermediate processing steps between simple corner detection and final corner type identification. The coordinate system establishment and grayscale value analysis act as intermediaries that transform basic corner detection data into detailed corner type information. This intermediary approach maintains relatively simple device structure while achieving high identification accuracy.
Solution Approach 2:
The patent performs preliminary actions by establishing a coordinate system and calculating grayscale values of quadrants before final corner type classification. These preliminary processing steps prepare the data in a form that enables accurate distinction between inner and outer corner points without requiring complex detection algorithms.
3Productivity
If the robot cleans all detected corner points to improve cleaning thoroughness, then the cleaning thoroughness is improved, but the cleaning time increases
Solution Approach 1:
The patent applies local quality by differentiating cleaning strategies for different corner types. Inner corner points and outer corner points are identified and can be cleaned with appropriate methods tailored to their specific characteristics. This localized approach ensures thorough cleaning of all corner points while optimizing the cleaning process for each type, reducing overall cleaning time.
Solution Approach 2:
The patent introduces dynamic classification of corner points into different types (inner and outer corners) based on their spatial characteristics and grayscale values. This dynamic classification enables the cleaning system to adapt its approach for different corner types, improving cleaning thoroughness while optimizing cleaning time through intelligent differentiation rather than uniform processing.
Data Source
AI summary
A method and an apparatus for controlling a robot, an electronic device, and a computer-readable storage medium. The control method includes: acquiring an environmental map obtained by detecting a current environment; detecting the environmental map to acquire at least one right angle corner point in the environmental map; determining a coordinate system in which the right angle corner point is located and using the right angle corner point of which the coordinate system satisfies a preset condition as a target right angle corner point; and controlling the robot to clean the target right angle corner point.