Robot Cleaner Path Segmentation to Reduce Map Regeneration Time
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Solution Overview
Problem
Robot cleaners face inefficiencies in calculating full travel paths and maintaining optimal cleaning performance as the area to be cleaned increases, requiring extensive memory and time to regenerate maps, especially when new areas are discovered.
Innovation Solution
A robot cleaner that divides the cleaning area into sub-areas, calculates and updates full paths based on connection points and travel paths within each sub-area, allowing for efficient path calculation and storage without regenerating the entire map, using a control unit with modules for area division, path generation, and obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot cleaner uses a traditional method to calculate the full travel path based on the entire cleaning map, then the cleaning coverage can be complete, but the calculation time increases significantly when the cleaning area increases
Solution Approach 1:
The cleaning map is divided into multiple sub-areas, and the full path is calculated by connecting paths within each sub-area rather than calculating the entire path at once. This segmentation reduces the computational complexity and time required for path calculation while maintaining complete cleaning coverage.
2Measurement precision
If the robot cleaner stores the complete cleaning map to calculate the full path, then the path calculation can be accurate, but the memory capacity requirement increases
Solution Approach 1:
Instead of storing the complete cleaning map in memory, the system stores only sub-area information and connection points. The full path is reconstructed by connecting these segmented elements, reducing memory requirements while maintaining path calculation accuracy.
3Productivity
If the robot cleaner regenerates the entire cleaning map when a new area is discovered, then the cleaning performance can be optimized, but the system complexity and time consumption increase
Solution Approach 1:
When a new area is discovered, the system adds only the new sub-area and its connection points to the existing path structure rather than regenerating the entire map. This segmented approach maintains optimal cleaning performance while reducing system complexity and computation time.
Data Source
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AI summary
The invention provides a method for controlling a robot cleaner being in an area to be cleaned, the area to be cleaned being divided into a plurality of sub-areas, a full path for the area to be cleaned being stored, the method comprising, when the area to be cleaned extends: generating (S310) a travel path within an extended area to be cleaned, adding (S330) the travel path within the extended area to be cleaned to the stored full path, searching for sub-areas adjacent the extended area to be cleaned, wherein the generating of the travel path within the extended area to be cleaned is performed to generate the travel path within the extended area to be cleaned from determined connection points with the adjacent sub-area.