Cleaning Robot Power-Aware Area Prioritization by Dirtiness Level
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Solution Overview
Problem
Existing cleaning robots lack intelligence in prioritizing cleaning tasks based on the dirtiness level of areas and power availability, often using a proximity-based approach that can lead to inefficient use of power and less effective cleaning.
Innovation Solution
A method and system for a cleaning robot that acquires a scene map and determines a target cleaning area based on dirtiness levels and current power, optimizing the cleaning path and power consumption by selecting areas with maximum or minimum dirtiness levels, and adjusting the cleaning process to ensure efficient use of power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the cleaning robot uses a proximity-based cleaning approach along a fixed route, then the cleaning process is simple to implement, but the cleaning efficiency and intelligence are reduced because different dirtiness levels of areas are not considered
Solution Approach 1:
The patent applies local quality by dividing the cleaning scene into different areas with different dirtiness levels (first dirtiness level for high dirtiness areas, second dirtiness level for low dirtiness areas). The cleaning robot selectively cleans areas based on their specific dirtiness characteristics, rather than applying a uniform cleaning approach throughout the entire scene. This resolves the contradiction by maintaining operational simplicity through route-based cleaning while improving efficiency through intelligent area selection based on dirtiness levels.
2Reliability
If the cleaning robot cleans all areas in the target scene, then the overall cleanliness is improved, but the power consumption increases and may exceed the available power
Solution Approach 1:
The patent applies partial action by selectively cleaning only certain areas (first cleaning area with high dirtiness level) when power is insufficient, rather than attempting to clean all areas. The system determines whether to clean all areas or only partial areas based on the comparison between available power and required power. This resolves the contradiction by ensuring cleaning reliability in priority areas while controlling power consumption within available limits.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting the cleaning strategy based on power availability. When power is sufficient, the robot cleans all areas; when power is insufficient, it switches to cleaning only high-priority areas. The system changes the cleaning parameter (coverage area) based on the power parameter, resolving the contradiction between maintaining cleanliness and controlling power consumption.
3Productivity
If the cleaning robot prioritizes cleaning areas with higher dirtiness levels, then the cleaning effectiveness is improved, but the complexity of determining cleaning priorities increases
Solution Approach 1:
The patent applies preliminary action by pre-dividing the cleaning scene into multiple areas with different dirtiness levels before the actual cleaning process. The system performs preliminary assessment and classification of areas (first dirtiness level vs. second dirtiness level) in advance, which simplifies the real-time decision-making during cleaning. This resolves the contradiction by improving cleaning effectiveness through priority-based selection while managing complexity through pre-established area classification.
Data Source
AI summary
A cleaning method and a cleaning robot are provided. The method includes: after the cleaning robot obtains a cleaning instruction for a target scene, acquiring a current power of the cleaning robot and a scene map for the target scene; if it is determined that the current power is insufficient to clean all areas to be cleaned in the target scene, determining a target cleaning area from all the areas to be cleaned in the target scene, based on a target dirtiness level for each of the areas to be cleaned; cleaning the target cleaning area based on the scene map, the target dirtiness level for the target cleaning area and the current power. A more intelligent cleaning robot and a more reasonable cleaning process are realized.