Pollution source determination robot cleaner and operating method thereof
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robot cleaners face challenges in identifying the current degree of pollution at each location without physically moving, leading to inefficient cleaning paths based solely on static pollution maps.
Innovation Solution
A robot cleaner equipped with a processor and memory that identifies pollution sources using a pollution map and object locations, allowing it to dynamically adjust its cleaning path based on real-time pollution data and event timelines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the robot cleaner sets a moving path based on a static pollution map, then the moving path optimization is achieved, but the current degree of pollution at each location is not reflected
Solution Approach 1:
The robot cleaner performs preliminary actions by identifying pollution sources among objects before executing the cleaning path. The processor identifies which objects are pollution sources based on the pollution map, and this preliminary identification enables the robot to optimize its moving path while reflecting current pollution conditions.
Solution Approach 2:
The system uses feedback by comparing the pollution map data with object location information to identify current pollution sources. This feedback mechanism allows the robot cleaner to adjust its moving path based on reflected current pollution degrees rather than relying solely on static map data.
2Measurement precision
If the robot cleaner directly moves to each location to identify pollution degree, then accurate pollution measurement is achieved, but cleaning efficiency is reduced
Solution Approach 1:
The robot cleaner uses a pollution map as a copy or representation of the actual pollution conditions in the environment. Instead of physically visiting each location to measure pollution, the system processes the pollution map data and object location information to identify pollution sources, thereby maintaining measurement precision while significantly improving cleaning efficiency.
3Device complexity
If the robot cleaner uses only static pollution map data, then path planning is simplified, but adaptability to changing pollution sources is poor
Solution Approach 1:
The system merges static pollution map data with dynamic object location information to identify pollution sources. By combining these two types of information, the robot cleaner achieves both simplified path planning (using the existing pollution map) and improved adaptability (by identifying current pollution sources among objects without increasing system complexity).
Data Source
AI summary
A robot cleaner is provided. The robot cleaner according to the disclosure includes a driver including a drive motor configured to cause the robot cleaner to move, a memory storing information on a pollution map for the degree of pollution for each location in a map corresponding to a place in which the robot cleaner is located and information on locations of a plurality of objects on the map, and a processor, wherein the processor is configured to: identify a pollution source among the plurality of objects based on information on the locations of the plurality of objects and the pollution map, and control the driver to move the robot cleaner based on the location of the identified pollution source on the map.