Robotic Cleaner Sub-Area Detection for Selective Sweeping
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Solution Overview
Problem
Current robotic cleaners lack efficient methods to autonomously identify and target specific areas within a space that require cleaning, often resulting in unnecessary sweeping and reduced operational efficiency.
Innovation Solution
A method and device that utilize environment imaging to acquire and analyze images of an area, determine sub-areas based on cleanliness thresholds, and control the robotic cleaner to reach and perform sweeping tasks in identified areas, enhancing precision and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the robotic cleaner performs automatic sweeping mode for the whole area, then the coverage area is maximized, but the sweeping efficiency is reduced due to unnecessary sweeping in already clean areas
Solution Approach 1:
The system performs preliminary action by capturing environment images and analyzing them to identify dirty sub-areas before the robotic cleaner begins sweeping. This allows the cleaner to target only areas that need cleaning, avoiding unnecessary sweeping in already clean areas while maintaining comprehensive coverage of the entire space.
2Reliability
If the robotic cleaner sweeps the entire area, then the cleanliness coverage is maximized, but the time consumption increases
Solution Approach 1:
The system applies local quality by dividing the entire area into multiple sub-areas based on environment image analysis, and identifying which specific sub-areas require cleaning. The robotic cleaner then focuses its sweeping operation only on the identified dirty sub-areas, ensuring that cleanliness is maintained in all necessary locations while significantly reducing the total time required compared to sweeping the entire area uniformly.
3Device complexity
If the robotic cleaner operates without image analysis, then the device complexity is minimized, but the ability to autonomously identify target areas is lost
Solution Approach 1:
The system introduces an intermediary component - the image analysis module - that processes environment images to identify dirty sub-areas. This intermediary layer enables the robotic cleaner to autonomously determine which areas require cleaning without requiring complex decision-making algorithms in the main controller, thus balancing enhanced automation with manageable system complexity.
Data Source
AI summary
A method and a device are provided for controlling a robotic cleaner. According to an example of the method, an environment image of an area may be acquired, and a sub-area to be swept in the area may be determined based on the environment image. Then, the robotic cleaner may be controlled to reach the sub-area to be swept and perform a sweeping task in the sub-area to be swept.