Moving robot and controlling method
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Solution Overview
Problem
Existing moving robots perform cleaning based solely on contamination levels, leading to redundant cleaning of highly contaminated areas and neglecting less contaminated regions, resulting in inefficient cleaning operations and uneven cleaning of indoor spaces.
Innovation Solution
A moving robot that determines contamination levels by counting the number of cleanings in each region and using dust sensor data to set cleaning and non-cleaning regions, preventing unnecessary repeated cleaning and ensuring uniform cleaning across the indoor area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If cleaning is performed based solely on contamination level, then highly contaminated regions are cleaned thoroughly, but cleaning time increases due to redundant cleaning and less contaminated regions are neglected
Solution Approach 1:
The cleaning area is divided into multiple regions, and each region is independently evaluated based on its contamination level and cleaning history. This segmentation allows the robot to selectively clean only the regions that need it, avoiding redundant cleaning of already clean areas while ensuring thorough cleaning of contaminated regions.
Solution Approach 2:
The robot performs a preliminary scanning phase before actual cleaning to detect and map contamination levels across all regions. Based on this preliminary information, it creates a cleaning plan that prioritizes regions needing cleaning, thus avoiding unnecessary cleaning operations and reducing overall cleaning time.
2Productivity
If the robot cleans based on contamination degree only, then cleaning priority is determined, but the same region is cleaned repeatedly causing redundant cleaning
Solution Approach 1:
The robot maintains a cleaning history database that records which regions have been cleaned and when. After each cleaning operation, the robot updates the status of cleaned regions. This feedback mechanism prevents the robot from re-cleaning regions that have already been cleaned, thereby eliminating redundant cleaning operations and improving overall cleaning efficiency.
Solution Approach 2:
The cleaning strategy dynamically adjusts based on real-time contamination detection and historical cleaning data. The robot continuously updates its cleaning plan by comparing current contamination levels with previous cleaning records, making the cleaning process adaptive and efficient rather than static and repetitive.
3Loss of time
If cleaning is performed only in highly contaminated regions, then cleaning time is reduced, but less contaminated regions are excluded from cleaning
Solution Approach 1:
The robot applies different cleaning strategies to different regions based on their specific contamination levels and cleaning histories. Highly contaminated regions receive thorough cleaning, while regions with lower contamination levels receive minimal or no cleaning. This localized approach ensures optimal cleaning coverage without wasting time on already clean areas.
Solution Approach 2:
The robot changes the cleaning parameters (such as cleaning intensity, duration, and frequency) based on the contamination level and cleaning history of each region. By dynamically adjusting these parameters, the robot achieves comprehensive cleaning coverage while minimizing unnecessary cleaning operations, thus balancing cleaning time and coverage.
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
The robot enhances cleaning efficiency by accurately determining dust levels in each region, preventing redundant cleaning and maintaining a uniform clean state across the entire indoor area.
Implementation Method 1
a dust sensor configured to detect dust in air suctioned during cleaning
Data Source
AI summary
A moving robot and a controlling method thereof are disclosed. The moving robot includes a dust sensor that detects dust in air suctioned during cleaning, and a controller that performs control so that the robot performs cleaning while traveling over a traveling area distinguished into a plurality of regions. The controller stores, in the data unit, dust information detected by the dust sensor and a number of times of cleaning in each region. The controller also sets a cleaning region and a non-cleaning region based on cleaning data, which is calculated based on the dust information and the number of times of cleaning. This helps prevent cleaning from being repeated unnecessarily and allows for cleaning depending on the number of times of cleaning, despite a small amount of dust. Accordingly, an entire indoor area may be maintained in a constant clean state and cleaning efficiency may be enhanced.